LISTA INICIAL DE REFERENCIAS ANDRÉS RODRIGO SAAVEDRA OSORIO TEMA AMPLIO: VIDA ARTIFICIAL(ALIFE), GENERACIÓN DE VIDA ARTIFICIAL Y MODELOS DE SIMULACION DE VIDA. En la siguiente URL se encontraron los siguientes artículos: http://www.cogs.susx.ac.uk/users/ezequiel/alife‐page/alife.html Compilación de bibliografía de Alife por Ezequiel Di Paolo. Donde está dividido en diferentes temas, de los cuales se extrajeron 5, los más relevantes, e interesantes. La división de temas es buena, pero sólo se categorizará para esta URL, en el filtrado final de referencias se hará una categorización similar o más depurada. ADAPTATIVE BEHAVIOR 1. Beer, R. D. (1996) Towards the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior In P. Maes, M. Mataric, J. Meyer, J. Pollack and S. Wilson (Eds.), From animals to animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (pp. 421‐429). MIT Press. [SAB96] Abstract Current debates regarding the possible cognitive implications of ideas from adaptive behavior research and dynamical systems theory would benefit greatly from a careful study of simple model agents that exhibit minimally cognitive behavior. This paper sketches one such agent, and presents the results of preliminary experiments on the evolution of dynamical neural networks for visually‐guided orientation, object discrimination and accurate pointing with a simple manipulator to objects appearing in its field of view.
2. Channon, A., (1998) Perpetuating evolutionary emergence SAB'98. [channon_ad_sab98_nc] Abstract Perpetuating evolutionary emergence is the key to arti_cially evolving increasingly complex systems. In order to generate complex entities with adaptive behaviors beyond our manual design capability, longterm incremental evolution with continuing emergence is called for. Purely arti_cial selection models, such as traditional genetic algorithms, are argued to be fundamentally inadequate for this calling and existing natural selection systems are evaluated. Thus some requirements for perpetuating evolutionary emergence are revealed. A new environment containing simple virtual autonomous organisms has been created to satisfy these requirements. Resulting evolutionary emergent behaviors are reported alongside of their neural correlates. In one example, the collective behavior of one species clearly provides a selective force which is overcome by another species, demonstrating the perpetuation of evolutionary emergence via naturally arising coevolution.
3. Channon, A., (1998) Evolving Novel Behaviors via Natural Selection In Proc. of the 6th International conference on Artificial Life, C. Adami, R.K. Belew, H. Kitano, C.E. Taylor (eds.) MIT Press. [channon_ad_alife6] Abstract The traditional _tness function based methodology of arti_cial evolution is argued to be inadequate for the construction of entities with behaviors novel to their designers. Evolutionary emergence via natural selection (without an explicit _tness function) is the way forward. This paper further considers the question of what to evolve, the focus being on principles of developmental modularity in neural networks. To develop and test the ideas, an arti_cial world containing autonomous organisms has been created and is described. Results show the developmental system to be well suited to long‐term incremental evolution. Novel emergent strategies are identi_ed both from an observer's perspective and in terms of their neural mechanisms.
4. Funes, P., Pollack, J. B. (2000). Measuring Progress in Coevolutionary Competition. From Animals to Animats 6: Proceedings of the Sixth International Conference on the Simulation of Adaptive Behavior. MIT Press Abstract Evolution, as trial‐and‐error based learning methods, usually relies on the repeatability of an experience: Different behavioral alternatives are tested and compared with each other. But agents acting on real environments may not be able to choose which experience to live. Instead, the environment provides varying initial conditions for each trial. In competitive games for example, it is difficult to compare players with each other if they are not able to choose their opponents. Here we describe a statistics‐ based approach to solving this problem, developed in the context of the Tron system, a coevolutionary experiment that matches humans against agents on a simple video game. We are now able to show, among the results, that the complex interactions led the artificial agents to evolve towards higher proficiency, while at the same time, individual humans learned as they gained experience interacting with the system. .
5. Harvey, I (1996) Relearning and Evolution in Neural Networks, In Adaptive Behavior vol. 4 no. 1 (1996) pp 79‐82. Abstract A recent paper in Adaptive Behavior _Nol__ Elman__ Parisi_ _____ reported simulations of populations of neural networks that evolve _to get _tter at one task_ at the population level and may also learn _a di_erent task_ at the individual level One result stated was that average _tness at the di_erent evolutionary task is improved when lifetime learning at the di_erent task is introduced A explanation will be proposed here for much of the data there presented that the main results are an artefact of the unconventional evolutionary algorithm used_ and can be interpreted rather di_erently as a form of relearning
SOCIAL BEHAVIOR 1. Di Paolo, E. A. (2000) Behavioral coordination, structural congruence and
entrainment in a simulation of acoustically coupled agents. Adaptive Behavior 8:1. Special issue on Simulation Models of Social Agents. K. Dautenhahn (guest ed.)
Abstract Approaching behaviour is studied in simulated agents interacting acoustically A genetic algorithm is used to evolve a fully recurrent_ continuous neural network for controlling the agents_ Evolved agents actively discriminate the location of external sources of sound_ Their own signaling behaviour is integrated with their search behaviour and sensor gain regulation through self_hearing_ Coupled agents show signs of structural congruence as they perform dancing patterns in space_ while the same agents behave very di_erently when acting on their own or in the presence of a source of sound that imitates their signal patterns.
2. Ficici, Sevan G. and Pollack, Jordan B. (1999). Statistical Reasoning Strategies in
the Pursuit and Evasion Domain. Fifth European Conference on Artificial Life. Dario Floreano, Jean‐Daniel Nicoud, Francesco Mondada, eds. Springer, 1999. Abstract Isaacs' treatise on differential games was a break‐through for the analysis of the pursuit‐and‐evasion (PE) domain within the context of strategies representable by differential equations. Current experimental work in Artificial Life steps outside of the formalism of differential games, but the formalism it steps into is yet to be identified. We introduce a formulation of PE that allows a formalism to be developed. Our game minimizes kinematic factors and instead emphasizes the informational aspect of the domain. We use information‐theoretic tools to describe agent behavior and implement a pursuit strategy based on statistical decision making; evaders evolved against this pursuit strategy exhibit a wide range of sophisticated behavior that can be quantitatively described. Agent performance is related to these quantifiables.
PDF http://www.demo.cs.brandeis.edu/papers/srsped_ecal99.pdf 3. Ficici, Sevan G. and Pollack, Jordan B. (1998). Coevolving Communicative
Behavior in a Linear Pursuer‐Evader Game. Proceedings of the Fifth International Conference of the Society for Adaptive Behavior. Pfeifer, Blumberg, Kobayashi, eds. Cambridge: MIT Press, 1998. Abstract The pursuer‐evader (PE) game is recognized as an important domain in which to study the coevolution of robust adaptive behavior and protean behavior (Miller & Cliff 1994). Nevertheless, the potential of the game is largely unrealized due to methodological hurdles in coevolutionary research raised by PE; versions of the game that have optimal solutions (Isaacs 1965) are closed‐ended, while other formulations are opaque with respect to their solution space, for the lack of a rigorous metric of agent behavior. This inability to characterize behavior, in turn, obfuscates coevolutionary dynamics. We present a new formulation of PE that affords a rigorous measure of agent behavior and system dynamics. The game is moved from the two‐dimensional plane to the one‐dimensional bitstring; at each time step, the evader generates a bit that the pursuer must simultaneously predict. Because behavior is expressed as a time series, we can employ information theory to provide quantitative analysis of agent activity. Further, this version of PE opens vistas onto the communicative component of pursuit and evasion behavior, providing an open‐ended serial communications channel and an open world (via coevolution). Results show that subtle changes to our game determine whether it is open‐ended, and profoundly affect the viability of arms‐race dynamics.
PDF
http://www.demo.cs.brandeis.edu/papers/LinearPE.pdf 4. Goldberg, D., Mataric, M.J., (1997) Interference as a Tool for Designing and
Evaluating Multi‐Robot Controllers, Proceedings, AAAI‐97, Providence, Rhode Island, July 27‐31, 1997, 637‐642. Abstract Designing and implementing cooperative group behaviors for robots is considered something of a black art involving an extensive amount of reprogramming and parameter adjustment_ What seems to be lacking is a pragmatic_ practical_ general_purpose tool that would both guide the design and structure the evaluation of controllers for distributed real_world multi_robot tasks_ In this paper_ we propose the use of interference between robots as one such simple tool for designing and evaluating multi_robot controllers_ We explore how key issues in multi_robot control can be addressed using interference_ a directly measurable property of amulti_robot system_ We discuss how behavior arbitration schemes_ i_e__ the choice of controllers_ can be made and adjusted using interference_ As an experimental example we demonstrate three di_erent implementations of a collection clean_up foraging_ task using four physical mobile robots_ and present analyses of the experimental data gathered from trials of all three implementations.
5. Hemelrijk, C. K. (1999) Effects Of Cohesiveness On Inter‐Sexual Dominance
Relationships And Spatial Structure Among Group‐Living Virtual Entities Fifth European Conference on Artificial Life (ed. D. Floreano, Nicoud, J‐D., Mondada, F.): Springer Verlag. Abstract Since male primates are bigger and stronger than females, they are by default considered dominant. When in a cohesively grouping ape (but not in its loosely grouping relative), females often appear dominant to males, the static image of female weakness is maintained and female dominance is attributed to high, species‐specific co‐operation among several females against single males. In this paper, an individual‐oriented model is used to produce a parsimonious alternative: female dominance over males may directly vary with group cohesiveness without species‐specific differences in co‐operative tendencies among females. The model consists of a homogeneous world in which entities roam. Entities are so constructed as to have merely a tendency to group and perform dominance interactions. ‘Male’ entities (StrongTypes) are characterised by a higher initial dominance value and intensity of attack than ‘female’ entities (called WeakTypes). Dominance values change and evolve due to the self‐reinforcing effects of winning and losing contests. In the model, more rank‐overlap between both types arises from a stronger feedback between dominance and spatial structure in cohesive than in looser groupings. Biological implications of these phenomena and testable hypotheses for real animals are discussed.
EVOLUTIONARY BIOLOGY 1. Abramson, G. (1997) Ecological model of extinctions Phys. Rev. E. 55, p 785
Abstract Abstract We present numerical results based on a simplified ecological system in evolution, showing features of extinction similar to that claimed for the biosystem on Earth. In the model each species consists of a population in interaction with the others, that reproduces and evolves in time. Each species is simultaneously a predator and a prey in a food chain. Mutations that change the interactions are
supposed to occur randomly at a low rate. Extinctions of populations result naturally from the predator‐ prey dynamics. The model is not pinned in a fitness variable, and natural selection arises from the dynamics.
2. Alvez, D., Fontanari, J.F., (1997) Error threshold in finite populations Preprint
Abstract Abstract A simple analytical framework to study the molecular quasispecies evolution of finite populations is proposed, in which the population is assumed to be a random combination of the constiyuent molecules in each generation,i.e., linkage disequilibrium at the population level is neglected. In particular, for the single‐sharp‐peak replication landscape we investigate the dependence of the error threshold on the population size and find that the replication accuracy at threshold increases linearly with the reciprocal of the population size for sufficiently large populations. Furthermore, in the deterministic limit our formulation yields the exact steady‐state of the quasispecies model, indicating then the population composition is a random combination of the molecules.
3. Bak, P., Paczuski, M., (1996) Mass Extinctions vs Uniformitarianism in Biological
Evolution. in Physics of Biological Systems Lecture Notes in Physics, Springer‐ Verlag. Abstract. Abstract It is usually believed that Darwin's theory leads to a smooth gradual evolution, so that mass extinctions must be caused by external shocks. However, it has recently been argued that mass extinctions arise from the intrinsic dynamics of Darwinian evolution. Species become extinct when swept by intermittent avalanches propagating through the global ecology. These ideas are made concrete through studies of simple mathematical models of coevolving species. The models exhibit self‐organized criticality and describe some general features of the extinction pattern in the fossil record.
4. Bedau, M. A., (1999) Quantifying the Extent and Intensity of Adaptive
Evolution. In A. Wu, ed., Proceedings of 1999 Genetic and Evolutionary Computation Conference Workshop Program (pp. 34‐37). Abstract Evolvability is the capacity to create new adaptations_ and especially new kinds of adaptations_ through the evolutionary process_ Evolvability is important both as a theoretical issue in biology and as a practical is_ sue in evolutionary computation_ But it is di_cult to study evolvability_ in part because it is di_cult to objectively and feasibly quantify evolvability in a gen_ eral enough way to compare it across di_erent evolving systems_ This paper is intended as an incremental step toward solving the problem of quantifying evolvability_ The progress here is only incremental because I do not ad_ dress the problem of quantifying evolvability per se_ rather_ I address the related problem of quantifying the degree to which a system exhibits adaptive evo_lution_ This is a step in the right direction_ though_ for two reasons_ First_ since evolvability is the capac_ ity to evolve new adaptations_ measuring a system_s adaptive evolution can tell you something about its evolvability_ Second_ since the method presented here is objective_ feasible_ and facilitates the quantitative comparison of adaptive evolution across a wide vari_ety of di_erent evolving systems_ it could spread those same virtues to the study of evolvability_ This paper explains a method for measuring adaptive evolution and then outlines how the method can be applied in the study of evolvability.
5. Bedau, M. A., Joshi, S., Lillie, B., (1999) Visualizing Waves of Evolutionary
Activity of Alleles. In A. Wu, ed., Proceedings of 1999 Genetic and Evolutionary Computation Conference Workshop Program (pp. 96‐98). Abstract We illustrate a method for visualizing adaptive evolutionary phenomena in evolving systems ____ The method was originally illustrated very briey and abstractly at the level of alleles ____ and it has sub sequently been applied in great detail at the level of whole genotypes ____ Here we apply the method in some signi_cant detail to alleles in three di_erent evolving systems_ a model of the evolution of sensory motor strategies_ a model of traders buying and selling securities in a _nancial market using an evolving set of marketforecasting rules_ and an analogue of the _ nancial market model in which natural selection is replaced by random selection_ The underlying hypoth esis behind the visualization method is that _activity wave diagrams_ highlight the quality of the main adaptive events and adaptive phenomena in an evolving system_ This abstract contains wave diagrams showing a variety of evolutionary phenomena such as com petetive exclusion_ cooperation_ and frozen accidents_
COMPLEX SYSTEMS AND NEURAL EVOLUTION 1. Barnett, L., (1997) Tangled Webs: Evolutionary Dynamics on Fitness Landscapes
with Neutrality, MSc dissertation, MSc in Evolutionary and Adaptive Systems, University of Sussex. September 1997. Abstract The bulk of research on the dynamics of populations of genotypes evolving on fitness landscapes has concentrated on the rôle of correlation and landscape ruggedness as a putative indicator of the qualitative dynamics. There is, however, a small but growing awareness amongst population geneticists (through Motoo Kimura's Neutral Theory of molecular evolution [16, 3]) and molecular biologists (Eigen, Schuster, et. al.[5, 2, 18]) of the importance of neutral mutation as a significant factor in evolutionary dynamics. This awareness has thus far not extended to the GA community. Of particular interest is the notion of neutral networks of selectively neutral genotypes which percolate a fitness landscape ‐ recent work on RNA folding landscapes characterises their structure in terms of such networks [21, 6, 20, 12, 13, 1]. There is at present a lack of computationally tractable abstract models demonstrating neutrality. In this paper we introduce two parametrised families of abstract landscapes: the NKp landscapes, based on the NK family of abstract landscapes [15], allow tuning of the degree of neutrality whilst leaving invariant the auto‐correlation function [24, 23, 15]. The RNN (Random Neutral Network) landscapes, constructed by mutually‐avoiding random walks, feature percolating neutral networks of specifiable size and neutral dimension. The statistical structure of these landscapes is examined and related to the characteristic dynamics of populations evolving on them. Several conjectures regarding the auto‐ correlation function on NKp landscapes (relevant also to NK landscapes) are raised. Attention is drawn to the very different nature of population dynamics on landscapes with percolating neutral networks as compared to the dynamics on rugged multi‐peaked landscapes. Qualitative similarities between population dynamics on RNN landscapes and RNA folding landscapes are highlighted. Finally, implications for biological research and for the application of GA's to optimisation problems are discussed.
2. Simulation of Self‐Reproducing Micelles using a Lattice‐Gas Automaton.
Authors: Peter V. Coveney (Schlumberger Cambridge Research), Andrew N. Emerton (Oxford), Bruce M. Boghosian (Boston University) Comments: 10 pages, LaTeX with epsf and REVTeX, EPS illustrations included Report-no: OU-THP-9613S, BU-CCS-960301
Subj-class: Soft Condensed Matter; Cellular Automata and Lattice Gases Journal-ref: J. Amer. Chem. Soc. 118 (1996) 10719-10724 Abstract We simulate self‐reproducing micellar systems using a recently introduced lattice‐gas automaton. This dynamical model correctly describes the equilibrium and non‐equilibrium properties of mixtures of oil, water and surfactants. The simulations reported here mimic the experiments of Luisi et al. in which caprylate micelles are formed by alkaline hydrolysis of immiscible ethyl caprylate ester. As in the laboratory experiments, we find an extended induction period during which the concentration of micelles remains small; thereafter the ester is consumed very rapidly with concomitant production of micelles.
PDF http://xxx.soton.ac.uk/PS_cache/cond‐mat/pdf/9709/9709183.pdf 3. Crutchfield, J. P.,(1994) The Calculi of Emergence: Computation, Dynamics, and
Induction, Physica D 75 (1994) 11‐54. Abstract Abstract Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be analyzed in terms of how model‐building observers infer from measurements the computational capabilities embedded in nonlinear processes. An observer’s notion of what is ordered, what is random, and what is complex inits environment depends directly on its computational resources: the amount of raw measurement data, of memory, and of time available for estimation and inference. The discovery of structure in an environment depends more critically and subtlely, though, on how those resources are organized. The descriptive power of the observer’s chosen (or implicit) computational model class, for example, can be an overwhelming determinant in finding regularity in data. This paper presents an overview of an inductive framework — hierarchical _‐machine reconstruction — in which the emergence of complexity is associated with the innovation of new computational model classes. Complexity metrics for detecting structure and quantifying emergence, along with an analysis of the constraints on the dynamics of innovation, are outlined. Illustrative examples are drawn from the onset of unpredictability in nonlinear systems, finitary nondeterministic processes, and cellular automata pattern recognition. They demonstrate how finite inference resources drive the innovation of new structures and so lead to the emergence of complexity.
4. Crutchfield, J. P.,(1994) Is Anything Ever New? Considering Emergence, in
Complexity: Metaphors, Models, and Reality, G. Cowan, D. Pines, and D. Melzner, editors, SFI Series in the Sciences of Complexity XIX, Addison‐Wesley, Redwood City (1994) 479‐497. Abstract Abstract This brief essay reviews an approach to defining and then detecting the emergence of complexity in nonlinear processes. It is, in fact, a synopsis of Reference [1] that leaves out the technical details in an attempt to clarify the motivations behind the approach. The central puzzle addressed is how we as scientists — or, for that matter, how adaptive agents evolving in populations — ever “discover” anything new in our worlds, when it appears that all we can describe is expressed in the language of our current understanding. One resolution — hierarchical machine reconstruction — is proposed. Along the way, complexity metrics for detecting structure and quantifying
emergence, along with an analysis of the constraints on the dynamics of innovation, are outlined. The approach turns on a synthesis of tools from dynamical systems, computation, and inductive inference.
5. The Evolutionary Design of Collective Computation in Cellular Automata
Authors: James P. Crutchfield, Melanie Mitchell, Rajarshi Das Comments: 49 pages, 20 figures Report‐no: Santa Fe Institute Working Paper 98‐09‐080 Subj‐class: Adaptation and Self‐Organizing Systems; Disordered Systems and Neural Networks; Biological Physics; Dynamical Systems; Pattern Formation and Solitons Abstract We investigate the ability of a genetic algorithm to design cellular automata that perform computations. The computational strategies of the resulting cellular automata can be understood using a framework in which ``particles'' embedded in space‐time configurations carry information and interactions between particles effect information processing. This structural analysis can also be used to explain the evolutionary process by which the strategies were designed by the genetic algorithm. More generally, our goals are to understand how machine‐learning processes can design complex decentralized systems with sophisticated collective computational abilities and to develop rigorous frameworks for understanding how the resulting dynamical systems perform computation.
PDF http://xxx.soton.ac.uk/PS_cache/adap‐org/pdf/9809/9809001.pdf MORPHOGENESIS AND DEVELOPMENT 1. Belew,R. K., Kammeyer, T. E., (1993) Evolving aesthetic sorting networks using
developmental grammars. In S. Forrest, editor, Proc. Fifth Intl. Conf. on Genetic Algorithms (ICGA‐93), page 629, San Mateo, CA, 1993. Morgan Kaufmann. Motivation We have had some success taking a second page from Natures book_ explicitly modelling a developmental process which transforms the genotypes manipulated by the GA into the phenotypes ultimately evaluated as solutions_We model development using a context_free grammar_ in which each production corresponds to a gene_
2. Eggenberger, P., Dravid, R. (1999) An Evolutionary Approach to Pattern
Formation Mechanisms on Lepidopteran WingsCongress on Evolutionary Computation 1999. Abstract In this paper an evolutionary and developmental model of cell differentiation and cell induction based on differential gene expression is introduced. By introducing morphogenetic gradients on a two‐ dimensional, cellular grid, the model is able to evolve and generate patterns resembling those found on moth and butterflies. Investigation of biological models has its interest for artificial evolution, because one can study the relationship between the genome and the phenotype.
PDF http://www.ifi.unizh.ch/ailab/people/dravid/publications/moth2.pdf 3. Eggenberger, P., (1997) Creation of Neural Networks Based on Developmental
and Evolutionary PrinciplesInternational Conference on Artificial Neural Networks ICANN'97, Lausanne, Switzerland, October 8‐10, 1997. Abstract In this paper we propose a biological inspired model to de velop the structure of arti_cial neural networks_ The model is based on an arti_cial genetic regualtory system_ which controls the development of the neural network_ The model allows for di_erent cell types which are the result of di_erent intercellular communication processes_ Having di_erent cells will lead to di_erent development of connection patterns_ The goal of the proposed model is to investigate the question how the local genetic processes are able to construct the structure of a neural network_
4. Furusawa, C., Kaneko, K,, (1998) Emergence of Rules in Cell Society:
Differentiation, Hierarchy, and StabilityBull. Math. Biol. Abstract Abstract A dynamic model for cell differentiation is studied, where cells with internal chemical reaction dynamics interact with each other and replicate. It leads to spontaneous differentiation of cells and determination, as is discussed in the isologous diversification. Following features of the differentiation are obtained: (1)Hierarchical differentiation from a ``stem'' cell to other cell types, with the emergence of the interaction‐dependent rules for differentiation; (2)Global stability of an ensemble of cells consisting of several cell types, that is sustained by the emergent, autonomous control on the rate of differentiation; (3)Existence of several cell colonies with different cell‐type distributions. The results provide a novel viewpoint on the origin of complex cell society, while relevance to some biological problems, especially to the hemopoietic system, is also discussed.
5. Gruau, F., Whitley, D. (1993) Adding Learning to the Cellular Development of
Neural Networks. Evolutionary Computation. Volume 1, No. 3 pp. 213‐233, 1993. Abstract A grammar tree is used to encode a cellular developmental process that can generate whole families of Boolean neural networks for computing parity and symmetry_ The development process resembles biological cell division_ A genetic algorithm is used to_nd a grammar tree that yields both architecture and weights specifying a particular neural network for solving speci_c Boolean functions_ The current study particularly focuses on the addition of learning to the development process and the evolution of grammar trees_ Three ways of adding learning to development process are explored_Two of these exploit the Baldwin e_ect by changing the _tness landscape without using Lamarckian evolution_ The third strategy is Lamarckian in nature_ Results for these three modes of combining learning with genetic search are compared against genetic search without learning_ Our results suggest that merely using learning to change the _tness landscape can be as e_ective as Lamarckian strategies at improving search.
EVOLUTION AND LEARNING 1. Blair, Alan D. and Sklar, Elizabeth (1999). Exploring evolutionary learning in a simulated hockey environment. 1999 Congress on Evolutionary Computation. Peter J. Angeline, Zbyszek Michalewicz, Marc Schoenauer, Xin Yao, Ali Zalzala, eds. . Abstract As a test‐bed for studying evolutionary and other machine learning techniques, we have developed a simulated hockey game called Shock in which players attempt to shoot a puck into their enemy's goal during a fixed time period. Multiple players may participate ‐‐ one can be controlled by a human user, while the others are guided by artificial controllers. In previous work, we introduced the Shock environment and presented players that received global input (as if from an overhead camera) and were trained on a restricted task, using an evolutionary hill‐climbing algorithm, with a staged learning approach. Here, we expand upon this work by developing players which instead receive input from local, Braitenberg‐style sensors. These players are able to learn the task with fewer restrictions, using a simpler fitness measure based purely on whether or not a goal was scored. Moreover, they evolve to develop robust strategies for moving around the rink and scoring goals.
PDF http://www.demo.cs.brandeis.edu/papers/shock_cec99.pdf 2. Cecconi, F. Menczer, F., Belew, R. K., (1995) Maturation and the evolution of imitative learning in artificial organisms. Technical Report CSE506, Computer Science &Engr. Dept., UC San Diego, La Jolla, CA 92093‐0114, 1995. Abstract Abstract The traditional explanation of delayed maturation age, as part of an evolved life history, focuses on the increased costs of juvenile mortality due to early maturation. Prior quantitative models of these trade‐ offs, however, have addressed only morphological phenotypic traits, such as body size. We argue that the development of behavioral skills prior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining the trade‐off for optimal age at maturity. Empirical support for this hypothesis from animal field studies is abundant. This paper provides further evidence drawn from simulation experiments. “Latent Energy Environments” (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolved according to a type of genetic algorithm. An advantage of this artificial world is that it becomes possible to discount all non‐behavioral costs of early maturity in order to focus on exclusively behavioral consequences. In spite of large selective costs imposed on parental fitness due to prolonged immaturity, the optimal age at maturity is shown to be significantly delayed when offspring are allowed to learn from their parents' behavior via imitation.
3. Chalmers D. (1990) The Evolution of Learning: An experiment in Genetic Connectionism Proceedings of the 1990 Connectionist Summer School Workshop. Abstract This paper explores how an evolutionary process can produce systems that learn. A general framework for the evolution of learning is outlined, and is applied to the task of evolving mechanisms suitable for supervised learning in single‐layer neural networks. Dynamic properties of a network’s information‐processing capacity are encoded genetically, and these properties are subjected to selective pressure based on their success in producing adaptive behavior in diverse environments. As a result of selection and genetic recombination, various successful learning mechanisms evolve, including the well‐known delta rule. The effect of environmental diversity on the
evolution of learning is investigated, and the role of different kinds of emergent phenomena in genetic and connectionist systems is discussed.
4. Ficici, Sevan G. and Pollack, Jordan B. (1998). Challenges in Coevolutionary Learning: Arms‐Race Dynamics, Open‐Endedness, and Mediocre Stable States. Proceedings of the Sixth International Conference on Artificial Life. Adami, Belew, Kitano, Talor, eds. Cambridge: MIT Press, 1998. Abstract Coevolution has been proposed as a way to evolve a learner and a learning environment simultaneously such that open‐ended progress arises naturally, via a competitive arms race, with minimal inductive bias. Nevertheless, the conditions necessary to initiate and sustain arms‐race dynamics are not well understood; mediocre stable states frequently result from learning through self‐play (Angeline & Pollack 1994), while analysis usually requires closed domains with known optima, like sorting‐networks (Hillis 1992). While intuitions regarding what enables successful coevolution abound, none have been methodically tested. We present a game that affords such methodical investigation. A population of deterministic string generators is coevolved with two populations of string predictors, one "friendly" and one "hostile"; generators are rewarded to behave in a manner that is simultaneously predictable to the friendly predictors and unpredictable to the hostile predictors. This game design allows us to employ information theory to provide rigorous characterizations of agent behavior and coevolutionary progress. Further, we can craft agents of known ability and environments of known difficulty, and thus precisely frame questions regarding learnability. Our results show that subtle changes to the game determine whether it is open‐ended, and profoundly affect the existence and nature of an arms race.
PDF http://www.demo.cs.brandeis.edu/papers/Challenges.pdf 5. Harvey, I., (1996) Is There Another New Factor in Evolution? Evolutionary Computation, Special Issue on Evolution, Learning, and Instinct: 100 Years of the Baldwin Effect v. 4, n. 3, pp. 311‐‐327, 1997. Abstract For ___ years it has been recognised that interactions between learning and evolution_ such as the Baldwin e_ect _Baldwin_ ______ can be subtle and often counter intuitive Recently a new e_ect has been discussed_ it is suggested that evolutionary progress towards one speci_c goal may be assisted by lifetime learning on a di_erent task which may or may not be uncorrelated_ _Parisi_ Nol__ _ Cecconi_ _____ Here the phenomenon is reproduced in a simple scenario where the tasks are indeed uncorrelated _ Another New Factor_ does indeed exist The e_ect is then explained as being due to recovery from weight perturbations_ caused by mutation_ in a neural network It is a special case of a recently discovered relearning e_ect _Harvey _ Stone_ ______ the spontaneous recovery of perturbed associations by learning uncorrelated tasks
ROBOTICS 1. Eggenberger, P. (1996) Cell interactions as a control tool of developmental
processes for evolutionary robotics. FROM ANIMALS TO ANIMATS 4, Fourth International Conference on Simulation of Adaptive Behavior, Cambridge, MA: The MIT Press/Bradford Books.
Abstract This paper describes new genetic and develop_mental principles for an arti_cial evolutionary sys_tem _AES_ and reports the _rst simulation re_sults_ Emphasis is placed on those developmental processes which reduce the length of the genome to code for a given problem_ We exemplify the usefulness of developmental processes with cell growth_ cell di_erentiation and the creation of neural control structures which we used to control a real world autonomous agent_ The importance of including developmental processes relies much on the fact that a neural network can be speci_ed implicitly by using cell_to_cell communication_
2. Ficici, Sevan G., Watson, Richard A. and Pollack, Jordan B. (1999). Embodied
Evolution: A Response to Challenges in Evolutionary Robotics. Eighth European Workshop on Learning Robots. Jeremy L. Wyatt, John Demiris, eds., 14‐22. Abstract We introduce Embodied Evolution (EE), a new methodology for conducting evolutionary robotics (ER). Embodied evolution uses a population of physical robots that evolve by reproducing with one another in the task environment. EE addresses several issues identified by researchers in the evolutionary robotics community as problematic for the development of ER. We review results from our first experiments and discuss the advantages and limitations of the EE methodology. PDF http://www.demo.cs.brandeis.edu/papers/ewlr8.pdf 3. Früh, H. Maris, M. (1996) NNetView: real world image processing and robot
control with a reentry neural network environment. (HTML) Tech Report 96.04, AI Lab, Dept. of Computer Science, University of Zürich. Abstract A new environment (NNetView) is presented which allows to control a robot with different sensors and a video camera using a comfortable large‐scale neural network with reentry connections. The software includes modules to read and digitize data from a color video camera and to control the serial port of the computer. Hebbian‐ and Anti‐Hebbian learning as well as value‐based learning are implemented. For the realization of temporal correlations, a time‐dimension is available. The source code is written in C++. The visual interface allows a user‐friendly handling of various objects and menu functions, and to construct complex network architectures in a visual programming style. Unit activity in 2‐dimensional unit arrays, connection strength and statistical data are directly visible. Meanwhile, several real‐world experiments were run on the NNetView environment, including edge detection, bilateral robot control, learning and optical flow.
4. Funes, P. and Pollack, J. (1998). Evolutionary Body Building: Adaptive physical
designs Artificial Life 4: 337‐357.
for
robots.
Abstract Creating artificial life forms through evolutionary robotics faces a "chicken and egg" problem: learning to control a complex body is dominated by problems specific to its sensors and effectors, while building a body that is controllable assumes the pre‐existence of a brain.
The idea of co‐evolution of bodies and brains is becoming popular, but little work has been done in evolution of physical structure because of the lack of a general framework for doing it. Evo‐lution of creatures in simulation has usually resulted in virtual entities which are not buildable, while embodied evolution in actual robotics is constrained by the slow pace of real time. The work we present takes a step in the problem of body evolution by applying evolutionary techniques to the design of structures assembled out of elementary components which stick together. Evolution takes place in a simulator which computes forces and stresses and predicts stability of 3‐ dimensional brick structures. The final printout of our program is a schematic assembly, which is then built physically. We demonstrate the functionality of this approach to robot body building with many evolved artifacts.
PDF http://www.demo.cs.brandeis.edu/papers/funpolalife.pdf 5. Harvey, I. (2000) Robotics: Philosophy of Mind using a Screwdriver In
Evolutionary Robotics: From Intelligent Robots to Artificial Life, Vol. III, T. Gomi (ed), AAI Books, Ontario, Canada, 2000. pp. 207‐230 Abstract The design of autonomous robots has an intimate relationship with the study of autonomous animals and humans _ robots pro_vide a convenient puppet show for illustrating current myths about cognition_ Like it or not_ any approach to the design of autonomous robots is underpinned by some philosophical position in the designer_Whereas a philosophical position normally has to survive in debate_in a project of building situated robots one_s philosophical position a_ects design decisions and is then tested in the real world _ _doing philosophy of mind with a screwdriver__Traditional Good Old Fashioned Arti_cial Intelligence GOFAI approaches have been based on what is commonly called a Cartesian split between body and mind _ though the division goes back at least to Plato_ The Dynamical Systems approach to cognition_ and to robot design_ draws on other philosophical paradigms_ We shall discuss how such varied philosophers as Heidegger_ Merleau_Ponty or Wittgenstein_ in the improbable event of them.
APPLICATIONS 1. Blair, Alan D. and Sklar, Elizabeth (1998). The evolution of subtle manoeuvres in simulated hockey. Proceedings of the Fifth International Conference of the Society for Adaptive Behavior. Pfeifer, Blumberg, Kobayashi, eds. Cambridge: MIT Press, 1998. Abstract We introduce a simulated hockey environment, called Shock, as a test bed for studying adaptive behaviour and evolution of robot controllers. A near‐frictionless playing surface is employed, partially mimicking zero gravity conditions. We show how a neural network using a simple evolutionary algorithm can develop nimble strategies for moving about the rink and scoring goals quickly and effectively.
Keywords: evolution, adaptive behaviour, robot controller, hockey. PDF http://www.demo.cs.brandeis.edu/papers/shock_sab98.pdf
2. Blair, Alan D. , Sklar, Elizabeth and Funes, Pablo (1998). Co‐evolution, Determinism and Robustness. In Simulated Evolution and Learning (SEAL‐98). Lecture Notes in Artificial Intelligence 1585. Bob McKay, Xin Yao, Charles S. Newton, Jong‐Hwan Kim, Takeshi Furahashi, eds., Springer‐Verlag. Abstract Robustness has long been recognised as a critical issue for co‐evolutionary learning. It has been achieved in a number of cases, though usually in domains which involve some form of non‐determinism. We examine a deterministic domain ‐‐ a pseudo real‐time two‐player game called Tron ‐‐ and evolve a neural network player using a simple hill‐climbing algorithm. The results call into question the importance of determinism as a requirement for successful co‐evolutionary learning, and provide a good opportunity to examine the relative importance of other factors.
PDF http://www.demo.cs.brandeis.edu/papers/tron_seal98.pdf 3. Funes, P. and Pollack, J. (1999). Computer Evolution of Buildable Objects. In Evolutionary Design by Computers. P. Bentley (editor). Morgan Kaufmann, San Francisco. pp. 387‐403. Abstract This chapter describes our work in evolution of buildable designs using miniature plastic bricks as modular components. Lego bricks are well known for their flexibility when it comes to creating low cost, handy designs of vehicles and structures. Their simple modular concept make toy bricks a good ground for doing evolution of computer simulated structures which can be built and deployed. .
PDF http://www.demo.cs.brandeis.edu/papers/edc98.pdf 4. Funes, P., Sklar, E., Juillé, H. and Pollack, J. (1998). Animal‐Animat Coevolution: Using the Animal Population as Fitness Function. Pfeifer, R. et. al. (eds.) From Animals to Animats 5: Proceedings of the Fifth International Conference on Simulation of Adaptive Behavior . MIT Press. pp 525‐533. Abstract We show an artificial world where animals (humans) and animats (software agents) interact in a coevolutionary arms race. The two species each use adaptation schemes of their own. Learning through interaction with humans has been out of reach for evolutionary learning techniques because too many iterations are necessary. Our work demonstrates that the Internet is a new environment where this may be possible through an appropriate setup that creates mutualism, a relationship where human and animat species benefit from their interactions with each other.
PDF http://www.demo.cs.brandeis.edu/papers/tronsab98.pdf
5. Hobbs, J., Husbands P., Harvey, I., (1996) Achieving Improved Mission Robustness In Proceedings of 4th ESA Workshop on Advanced Space Technologies for Robotic Applications, ASTRA 96, European Space Agency 1996. Abstract This paper gives background to and outlines a proposed programme of work aimed at exploring biologically inspired approaches to developing a potentially spaceworthy planetary exploration vehicle_ A major consideration is in achieving a very high high degree of robustness and reliability_ In order to develop an improved system level mission design_ an integration of evolutionary robotics and _traditional_ space mission design methodologies is proposed_
PHILOSOPHY 1. Lifeworld Analysis. Authors: P. Agre, I. Horswill Comments: See this http URL for any accompanying files Subj-class: Artificial Intelligence Journal-ref: Journal of Artificial Intelligence Research, Vol 6, (1997), 111-145 Abstract We argue that the analysis of agent/environment interactions should be extended to include the conventions and invariants maintained by agents throughout their activity. We refer to this thicker notion of environment as a lifeworld and present a partial set of formal tools for describing structures of lifeworlds and the ways in which they computationally simplify activity. As one specific example, we apply the tools to the analysis of the Toast system and show how versions of the system with very different control structures in fact implement a common control structure together with different conventions for encoding task state in the positions or states of objects in the environment.
2. Baas, N.A., Emmeche, C. (1997), On emergence and explanation, 12 pp., SFI Working Paper 97-02-008. Santa Fe Institute. Abstract Emergence is a universal phenomenon that can be defined mathematically in a very general way. This is useful for the study of scientifically legitimate explanations of complex systems, here defined as hyperstructures. A requirement is that the observation mechanisms are considered within the general framework. Two notions of emergence are defined, and specific examples of these are discussed.
3. Bedau, M. A., (1999) Can Unrealistic Computer Models Illuminate Theoretical Biology? In A. Wu, ed., Proceedings of 1999 Genetic and Evolutionary Computation Conference Workshop Program (pp. 20-23). Abstract Questions about the important essential properties of biological systems are both di_cult to answer and worthwhile to try to answer_ Here are three examples of deep open questions in theoretical biology_ Is robust multi_level emergent activity an intrin_sic property of certain homeostatic self_organizing systems like cells or organisms_ and if so_ how is this possible_ Is open_ended adaptive evolution an intrinsic property of certain evolving systems like the bio_sphere_ and if so_ how_Is unbounded complexity or diversity growth an intrinsic property of certain evolving systems like the biosphere_ and if so_ how.
4. Bedau, M. A., (1999) Supple Laws in Biology and Psychology. In Where Biology Meets Psychology: Philosophical Essays, V. Hardcastle, ed., MIT Press, 1999. pp. 287-302.
Abstract The nature and status of psychological laws are a long‐standing controversy. I will argue that part of the controversy stems from the distinctive nature of an important subset of those laws, which I’ll call “supple laws.” An emergent‐model strategy taken by the new interdisciplinary field of artificial life provides a strikingly successful understanding of analogously supple laws in biology. So, after reviewing the failures of the two evident strategies for understanding supple psychological laws, I’ll turn for inspiration to emergent‐models explanations of supple laws in biology. I’ll conclude by inferring what an emergent model of supple laws in psychology should be like.
5. Di Paolo, E. (1996) Some False Starts in the Construction of a Research Methodology for Artificial Life. Noble, J., Parsowith, S. (eds.) The 9th White House Papers: Graduate Research in the Cognitive and Computing Sciences at Sussex. University of Sussex, School of Cognitive and Computing Sciences. Abstract This article briefly reviews some guidelines for building a research methodology in Artificial Life given by Miller (Miller, 1995). A formal argument is presented to point at some problems arising from the systematic application of these guidelines given the current state of affairs in Theoretical Biology, and some practical arguments are proposed against the downsizing strategy adopted by Miller.
http://citeseer.ist.psu.edu/packard00artificial.html En la URL de citeseer se encontraron los artículos base para el inicio de la investigación, que junto con los de la anterior colección de referencias, pueden servir como una base interesante para la labor a seguir.
CITESEER: LISTA DE ARTICULOS 1. Artificial Life (2000) (Make Norman H. Packard, Mark. A. Bedau
Corrections) (174 citations)
Abstract This article provides a current snapshot and highlights some of the controversies. Encyclopedia of Cognitive Science 'Copyright Macmillan Reference Ltd 15 September, 2000 Page 3 C. G. Langton. Artificial Life. In C. G. Langton, editor, Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity, pages 1‐‐44, Redwood City, 1989. Addison‐Wesley. http://citeseer.ist.psu.edu/packard00artificial.html
PDF en: http://citeseer.ist.psu.edu/cache/papers/cs/16711/http:zSzzSzwww.reed.eduzSz~mab zSzpaperszSzECS.pdf/packard00artificial.pdf 2. Artificial Life Needs a Real Epistemology Corrections) (12 citations) H. H. Pattee. European Conference on Artificial Life
(1995) (Make
Abstract Foundational controversies in artificial life and artificial intelligence arise from lack of decidable criteria for defining the epistemic cuts that separate knowledge of reality from reality itself, e.g., description from construction, simulation from realization, mind from brain. Selective evolution began with a description‐construction cut, i.e., the genetically coded synthesis of proteins.
Pattee H.H. 1995. Artificial Life Needs a Real Epistemology, in Moran F., et al.(eds.), Advances in Artif. Life. Berlin: Springer, pp. 23‐‐38. http://citeseer.ist.psu.edu/pattee95artificial.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/12112/http:zSzzSzwww.ssie.binghamton.e duzSzpatteezSzaepistem.pdf/pattee95artificial.pdf 3. Mutualism Promotes Diversity and Stability in a Simple Artificial Ecosystem (2002) (Make Corrections) Elizaveta Pachepsky, Tim Taylor, Stephen Jones Abstract This work investigates the effect of ecological interactions between organisms on the evolutionary dynamics of a community. A spatially explicit, individual based model is presented, in which organisms compete for space and for resources. We investigated how introducing the potential for mutualistic relationships (where the presence of one type of organism stimulates the growth of another type, and vice versa) affected the evolutionary dynamics of the system.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/26553/http:zSzzSzwww.dai.ed.ac.ukzSz homeszSztimtzSzresearchzSz..zSzpaperszSzpachepsky_final.pdf/pachepsky02mutuali sm.pdf 4. Recent Developments in the Evolution of Morphologies and Controllers for Physically Simulated Creatures (2001) (Make Corrections) (8 citations) Tim Taylor, Colm Massey Abstract
Karl Sims' work on evolving body shapes and controllers for three dimensional, physically simulated creatures generated wide interest on its publication in 1994. The purpose of this paper is threefold: (1) to highlight a spate of recent work by a number of researchers in replicating, and in some cases extending, Sims' results using standard PCs (Sims' original work was done on a Connection Machine CM‐ 5 parallel computer).
Tim Taylor and Colm Massey. Recent developments in the evolution of morphologies and controllers for physically simulated creatures. Artificial Life, 7(1):77‐‐87, 2001. http://citeseer.ist.psu.edu/taylor01recent.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/25919/http:zSzzSzwww.dai.ed.ac.ukzSz homeszSztimtzSzresearchzSz..zSzpaperszSzTaylor‐ RecentDevelopments.pdf/taylor01recent.pdf 5. A Virtual Creatures Model for Studies in Artificial Evolution (2005) (Make Corrections) (1 citation) Thomas Miconi, Alastair Channon Abstract This article we describe our own model for the evolution of artificial creatures in a physically realistic 3D environment. This model is broadly similar to Sims', but with important differences. Our work brings three contributions Oscillators in general are ubiquitous in physics and biology, and might be argued to be fundamental elements in their own right;
T. Miconi and A. Channon. A virtual creatures model for studies in artificial evolution. In IEEE Congress on Evolutionary Computation (CEC 2005), 2005. http://citeseer.ist.psu.edu/miconi05virtual.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs2/39/http:zSzzSzwww.cs.bham.ac.ukzSz ~txmzSz.zSzcec2005.pdf/miconi05virtual.pdf 6. Evolution of Thomas Miconi
Intelligent
Agents
(2005) (Make
Corrections)
Abstract This report is taken from the paper submitted to the CEC conference
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/39/http:zSzzSzwww.cs.bham.ac.ukzSz ~txmzSz.zSzreport4.pdf/miconi05evolution.pdf
7. Evolution in Natural and Artificial Systems (2004) (Make Corrections) Thomas Miconi Abstract The goal of this research is to study the conditions in which evolution may lead to the sustained emergence of novel behaviours, and how this may be applied to the automatic design of complex entities. We argue that with regard to artificial evolution, this field of study has been rather overlooked, with a preference given to mathematical or experimental results based on abstract selection models.
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/273/http:zSzzSzwww.cs.bham.ac.ukzS z~txmzSz.zSztpshort.pdf/miconi04evolution.pdf 8. From Artificial Evolution Corrections) (9 citations) Timothy John Taylor
to
Artificial
Life
(1999) (Make
Abstract This work addresses the question: What are the basic design considerations for creating a synthetic model of the evolution of living systems (i.e. an `artificial life' system)? It can also be viewed as an attempt to elucidate the logical structure (in a very general sense) of biological evolution. However, with no adequate definition of life, the experimental portion of the work concentrates on more specific issues, and primarily on the issue of open‐ended evolution.
Tim Taylor. From Artificial Evolution to Artificial Life. Unpublished PhD thesis, Division of Informatics, University of Edinburgh, 1999. http://citeseer.ist.psu.edu/taylor99from.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/25938/http:zSzzSzls11‐ www.informatik.uni‐ dortmund.dezSzpeoplezSzbanzhafzSzac_review.pdf/dittrich00artificial.pdf 9. Artificial Chemistries Peter Dittrich
(2000) (Make
Corrections) (1 citation)
Abstract An artificial chemistry is, in a broad sense, a man‐made system which is similar to a chemical system. More precisely ‐‐ but not covering every type ‐‐ an artificial chemistry can be defined by a set of objects and a set of reaction rules which specify how the objects interact. The tutorial focuses on abstract artificial chemistries where there is no direct one‐to‐one relationship between artificial and real chemistry on the molecular/object and reaction/interaction level.
Dittrich, P. (2000). On Artificial Chemistries (working title). Ph. D. thesis, University of Dortmund. (in preparation). http://citeseer.ist.psu.edu/article/dittrich00artificial.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/10234/http:zSzzSzls11‐ www.informatik.uni‐ dortmund.dezSzpeoplezSzdittrichzSzzSzpzSzDit99.pdf/dittrich00artificial.pdf 10. Artificial Chemistries A Review (2000) (Make Corrections) (6 citations) Peter Dittrich, Jens Ziegler, Wolfgang Banzhaf Artificial Life Abstract: This article reviews the growing body of scientific work in Artificial Chemistry. First, common motivations and fundamental concepts are introduced. Second, current research activities are discussed along three application dimensions: modelling, information processing and optimization. Finally, common phenomena among the different systems are summarized. It is argued here that Artificial Chemistries are "the right stuff" for the study of pre‐biotic and bio‐chemical evolution, and they provide a ... (Update) Peter Dittrich, Jens Ziegler, and Wolfgang Banzhaf. Artificial chemistries ‐ a review. Artificial Life, 7(3):225‐‐275, 2001. http://citeseer.ist.psu.edu/article/dittrich00artificial.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/25938/http:zSzzSzls11‐ www.informatik.uni‐ dortmund.dezSzpeoplezSzbanzhafzSzac_review.pdf/dittrich00artificial.pdf 11. BioSonics: Sensual Explorations of a Complex System (2004) (Make Corrections) Daniel Bisig Abstract Complex systems abound in nature and are becoming increasingly important in artificial systems. The understanding and controlling of such systems is a major challenge. This paper tries to take a fresh approach to these issues by describing an interactive art project that involves cross‐modal interaction with a complex system. By combining sound and vision, the temporal and spatial dynamics of the system are conveyed simultaneously.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/30314/http:zSzzSzwww.iuiconf.orgzSz0 4pdfzSz2004‐002‐0018.pdf/bisig04biosonics.pdf
12. Real Evolution Peter Dittrich
in
Artificial
Chemistries (Make
Corrections)
Abstract Introduction to Artificial Chemistries An artificial chemistry is an artificial system, which is similar to a chemical system. Usually, an artificial chemistry consists of: 1. a set of objects S : These objects may be abstract symbols [16], character sequences [1, 12, 14], lambda‐expressions [8], binary strings [3, 6, 15], numbers [4], or proofs [10]. 2. a set of rules R, describing the interaction among objects.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/10234/http:zSzzSzls11‐ www.informatik.uni‐dortmund.dezSzpeoplezSzdittrichzSzzSzpzSzDit98.pdf/real‐ evolution‐in‐artificial.pdf 13. Artificial Chemistries Peter Dittrich, Jens Ziegler
(1998) (Make
Corrections) (1 citation)
Abstract Introduction to Artificial Chemistries An artificial chemistry is an artificial system, which is similar to a chemical system. Bagley and Farmer write in [1]: An artificial chemistry is a set of rules stating which catalyzed reactions occur and with what strength.
Dittrich, P. (2000). On Artificial Chemistries (working title). Ph. D. thesis, University of Dortmund. (in preparation). http://citeseer.ist.psu.edu/231629.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/10234/http:zSzzSzls11‐ www.informatik.uni‐ dortmund.dezSzpeoplezSzdittrichzSzzSzpzSzDZ98gwal3.pdf/artificial‐chemistries.pdf 14. Artificial Chemistries A Review (2001) (Make Corrections) (6 citations) Peter Dittrich, Jens Ziegler, Wolfgang Banzhaf Abstract This article reviews the growing body of scientific work in artificial chemistry.
Peter Dittrich, Jens Ziegler, and Wolfgang Banzhaf. Artificial chemistries ‐ a review. Artificial Life, 7(3):225‐‐275, 2001. http://citeseer.ist.psu.edu/article/dittrich01artificial.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/29770/http:zSzzSzls11‐ www.informatik.uni‐dortmund.dezSzpeoplezSzzieglerzSzALIFE2001zSzartificial‐ chemistry‐review.pdf/dittrich01artificial.pdf
15. Evolving a "Nose" for a Robot (2000) (Make Corrections) Jens Ziegler, Wolfgang Banzhaf Evolution of Sensors in Nature, Hardware, and Abstract: The evolution of metabolisms that act as control programms for a small robot leads to the selection of most relevant sensory information. The underlying artificial chemistry evolves efficient information processing pathways with most benefit for the desired task, robot navigation.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/29769/http:zSzzSzls11‐ www.informatik.uni‐ dortmund.dezSzpeoplezSzzieglerzSzGECCO2000zSzZB_GECCO.pdf/ziegler00evolving.p df 16. The COSMOS Artificial Life System (1997) (Make Corrections) (1 citation) Tim Taylor Abstract This paper describes the COSMOS
Taylor, T. 1997. The COSMOS artificial http://citeseer.ist.psu.edu/article/taylor97cosmos.html More
life
system.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/6401/http:zSzzSzwww.dai.ed.ac.ukzSzdaid bzSzhomeszSztimtzSzpaperszSzcosmos‐tech‐v1n1.pdf/taylor97cosmos.pdf 17. A Transformation Framework for Solving Artificial Life Systems Palem GopalaKrishna (2005) (Make Corrections) (1 citation) Palem GopalaKrishna Abstract Mathematically a system is said to be solved if its future states can be predicted from the information provided by the present and past state history. In this paper, we examine the problem of solving Artificial Life systems using the principles of statemachines.
Palem GopalaKrishna. A transformation framework for solving artificial life systems. Submitted to Evolutionary Computation, 2005. http://citeseer.ist.psu.edu/gopalakrishna05transformation.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs2/742/http:zSzzSzwww.cse.iitb.ac.inzSz~ krishnazSzALSystemsFramework.pdf/gopalakrishna05transformation.pdf
18. On Modelling Chris Adami
Life
(1994) (Make
Corrections) (9 citations)
Abstract We present a theoretical as well as experimental investigation of a population of self‐replicating segments of code subject to random mutation and survival of the fittest. Under the assumption that such a system constitutes a minimal system with characteristics of life, we obtain a number of statements on the evolution of complexity and the trade‐off between entropy and information.
C. Adami, "On Modelling Life", http://citeseer.ist.psu.edu/adami94modelling.html
these
proceedings. More
PDF http://citeseer.ist.psu.edu/cache/papers/cs/2526/ftp:zSzzSzftp.krl.caltech.eduzSzpu bzSzavidazSzoml.pdf/adami94modelling.pdf 19. Even Turing Machines Can Compute Uncomputable Functions (1998) (Make Corrections) (4 citations) B. Jack Copeland Unconventional Models of Computation, Springer, 1998 Abstract Accelerated Turing machines are Turing machines that perform tasks commonly regarded as impossible, such as computing the halting function. The existence of these notional machines has obvious implications concerning the theoretical limits of computability. 2 1. Introduction Neither Turing nor Post, in their descriptions of the devices we now call Turing machines, made much mention of time (Turing 1936, Post 1936).
Copeland, B.J. 1998. 'Even Turing Machines Can Compute Uncomputable Functions'. In Calude, C.S., Casti, J., Dinneen, M.J. (eds) 1998, Unconventional Models of Computation, Singapore: Springer‐Verlag. http://citeseer.ist.psu.edu/copeland98even.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/18885/http:zSzzSzwww.phil.canterbury .ac.nzzSzphilsitezSzpeoplezSzjackzSzpubzSzevenzSzeven.pdf/copeland98even.pdf 20. Super Turing‐Machines (Make B. Jack Copeland
Corrections) (3 citations)
Abstract To a practical application. A dozen years later the first stored‐program electronic digital computers began to spring into existence. All were modelled on the universal Turing machine. Today's digital
computers also are in essence universal Turing machines. 2. Is There a Known Upper Bound to Computability?
Copeland, B.J. 1998d. 'Super Turing‐Machines'. Complexity, 4 (October). http://citeseer.ist.psu.edu/387923.html More PDF
http://citeseer.ist.psu.edu/cache/papers/cs/18885/http:zSzzSzwww.phil.canterbury.ac .nzzSzphilsitezSzpeoplezSzjackzSzpubzSzsuper.pdf/super‐turing‐machines.pdf 21. The Artificial Evolution of Real Intelligence by Natural Selection (Make Corrections) (1 citation) Alastair Channon, Bob Damper Abstract This paper outlines a preliminary step towards the long‐term goal of intelligent artificial life. Evolutionary emergence via natural selection is proposed as the way forward, in combination with other biologically‐inspired principles including the developmental modularity of neural networks. In order to develop and test the ideas, an artificial world containing autonomous organisms has been created.
Channon A., The Artificial Evolution of Real Intelligence by Natural Selection, Image, Speech & Intelligent Systems Research Group, University of Southampton. http://www.soton.ac.uk/~adc96r http://citeseer.ist.psu.edu/169074.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/5677/ftp:zSzzSzftp.cogs.susx.ac.ukzSzpu bzSzecal97zSzonlinezSzF128.pdf/the‐artificial‐evolution‐of.pdf 22. The Artificial Life Roots of Corrections) (71 citations) Luc Steels
Artificial
Intelligence
(1993) (Make
Abstract Behavior‐oriented AI is a scientific discipline that studies how behavior of agents emerges and becomes intelligent and adaptive. Success of the field is defined in terms of success in building physical agents that are capable of maximising their own self‐preservation in interaction with a dynamically changing environment.
L. Steels, "The Artificial Life Roots of Artificial Intelligence", Artificial Life, vol. 1, pp. 75‐‐ 110, 1994. http://citeseer.ist.psu.edu/steels93artificial.html More PDF
http://citeseer.ist.psu.edu/cache/papers/cs/42/http:zSzzSzarti.vub.ac.bezSzwwwzSz krestzSzrobotzSzalife.pdf/steels93artificial.pdf 23. Intelligence Without Reason (1991) (Make Corrections) (458 citations) Rodney A. Brooks. Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI‐91) Abstract Computers and Thought are the two categories that together define Artificial Intelligence as a discipline. It is generally accepted that work in Artificial Intelligence over the last thirty years has had a strong influence on aspects of computer architectures. In this paper we also make the converse claim; that the state of computer architecture has been a strong influence on our models of thought.
Brooks, R. A. (1991), Intelligence Without Reason, in `Proceedings, IJCAI‐91', Sydney, Australia. http://citeseer.ist.psu.edu/article/brooks91intelligence.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/314/http:zSzzSzwww.cs.mu.oz.auzSzisa zSzbrooks91.pdf/brooks91intelligence.pdf 24. A Taxonomy of Multimodal Interaction in the Human Information Processing System (1995) (Make Corrections) (7 citations) L. Schomaker, J. Nijtmans, et al. Abstract This document has been prepared in the ESPRIT BRA No. 8579, Multimodal Integration for Advanced Multimedia Interfaces ‐‐‐ in the following referred to as ‐‐‐ in order to serve as a basis for future work. The basic terms which will be used in will be defined and an overview on man‐machine‐interfaces will be given.
L. Schomaker, J. Nijtmans, A. Camurri, F. Lavagetto, P. Morasso, C. Benoit, T. Guiard‐ Marigny, B. LeGoff, J. Robert‐Ribes, A. Adjoudani, I. Def'ee, S. Munch, K. Hartung, and J. Blauert. A taxonomy of multimodal interaction in the human information processing system. Technical report, Esprit Project 8579 MIAMI, February 1995. http://citeseer.ist.psu.edu/schomaker95taxonomy.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs2/358/http:zSzzSzwww.ai.rug.nlzSz~lam bertzSzpaperszSzTaxonomyMultimodalInteraction‐RepEsprit‐Project8579‐ MIAMI.pdf/schomaker95taxonomy.pdf 25. Artificial Life and Real Robots (1992) (Make Corrections) (83 citations) Rodney A. Brooks. European Conference on Artificial Life Abstract
The first part of this paper explores the general issues in using Artificial Life techniques to program actual mobile robots. In particular it explores the difficulties inherent in transferring programs evolved in a simulated environment to run on an actual robot. It examines the dual evolution of organism morphology and nervous systems in biology.
Rodney A. Brooks. Artificial life and real robots. In F. J. Varela and P. Bourgine, editors, Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life, pages 3‐‐10. MIT Press/Bradford Books, Cambridge, MA, 1992. http://citeseer.ist.psu.edu/brooks92artificial.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/1309/http:zSzzSzwww.ai.mit.eduzSzpeo plezSzbrookszSzpaperszSzreal‐robots.pdf/brooks92artificial.pdf 26. Computational Autopoiesis: Corrections) (4 citations) Barry McMullin
The
Original
Algorithm
(1997) (Make
Abstract This report presents a detailed review and re‐presentation of the algorithm for (computational) realisation of autopoiesis, originally presented by Varela, Maturana & Uribe (1974). The review is from the perspective of one seeking to re‐implement this algorithm. It arises from an on‐going project to develop such a re‐implementation using the Swarm simulation system.
McMullin, B. (1997), Computational Autopoiesis: The Original Algorithm, Technical Report 97‐01‐001, Santa Fe Institute, Santa Fe, NM 87501, USA. http://citeseer.ist.psu.edu/mcmullin97computational.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/1815/http:zSzzSzwww.santafe.eduzSzsf izSzpublicationszSzWorking‐PaperszSz97‐01‐ 001zSzbmcm9701.pdf/mcmullin97computational.pdf 27. Cybernetics (1998) (Make Cliff Joslyn, Francis Heylighen
Corrections)
Abstract Margaret Mead. Hosted by the Josiah Macy Jr. Foundation, these became known as the Macy Conferences on Cybernetics [11]. Through the 1950s, Cybernetic thinkers came to cohere with the school of General Systems Theory (GST), founded at about the same time by Ludwig von Bertalanffy [12, 33], as an attempt to build a unified science by uncovering the common principles that govern open, evolving systems.
PDF
http://citeseer.ist.psu.edu/cache/papers/cs/8343/ftp:zSzzSzwwwc3.lanl.govzSzpubz SzuserszSzjoslynzSzenccs2.pdf/joslyn98cybernetics.pdf 28. Intelligence (Make Corrections) Towards Measures Based Semiotic Control Dr. Cliff Joslyn Computer Research... Abstract We address the question of how to identify and measure the degree of intelligence in systems. We define the presence of intelligence as equivalent to the presence of a control relation. We contrast the distinct atomic semioic definitions of models and controls, and discuss hierarchical and anticipatory control.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/25149/ftp:zSzzSzwwwc3.lanl.govzSzpub zSzuserszSzjoslynzSzmetrics00.pdf/intelligence.pdf 29. Four Puzzles about Life Mark A. Bedau. Artificial Life
(1998) (Make
Corrections) (3 citations)
Abstract To surmount the notorious difficulties of defining life, we should evaluate theories of life not by whether they provide necessary and sufficient conditions for our current preconceptions about life but by how well they explain living phenomena and how satisfactorily they resolve puzzles about life.
Bedau, M. A. 1997. Four puzzles about life. Lecture presented at a conference on the Philosophy of Artificial Life, PAL97, Christ Church College, Oxford University, March 1997. http://citeseer.ist.psu.edu/bedau98four.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/8501/http:zSzzSzwww.reed.eduzSz~ma bzSzpaperszSz4.puzzles.pdf/bedau98four.pdf 30. Supple Laws Mark A. Bedau
in
Psychology
and
Biology (Make
Corrections)
Abstract Ications. A variety of factors bring about the need for ceteris paribus qualifications in psychological laws. People sometimes fail to infer what is implied by their antecedent beliefs because of inattention or illogic, but some exceptions to the law of Pure Reason reflect attentive logical acumen at its best.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/8501/http:zSzzSzwww.reed.eduzSz~ma bzSzpaperszSzish.pdf/supple‐laws‐in‐psychology.pdf
31. Sui Generis (Make Corrections) Real Causal Factor Chapter 5. Teleological Reductionism: Is there a need for Aristotelian... Abstract Sui generis real causal factor in the world is the correct understanding of teleological causation. I will argue further that sui generis teleological causation is both philosophically and scientifically acceptable given a proper understanding of the methodological and ontological commitments of modern science.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/16854/http:zSzzSzwww.colorado.eduzS zphilosophyzSzfaczSzcameronzSzdisszSzdissc5.pdf/sui‐generis.pdf 32. The Problem Rich Cameron
of
Life's
Definition (Make
Corrections)
Abstract r (1984). 2 See Bedau (1992b); also Sober (1992) for necessary qualifications to the claim. It is perhaps best to let some of Artifical Life's (AL) leading practitioners describe the nature of AL research. Bonabeau and Theraulaz define AL thus: "We consider it as a general method consisting in generating at a macroscopic level, from microscopic, generally simple, interacting components, behaviors that are interpretable as lifelike" (1995, 303).
PDF http://citeseer.ist.psu.edu/cache/papers/cs/16854/http:zSzzSzwww.colorado.eduzS zphilosophyzSzfaczSzcameronzSzdisszSzdissc1.pdf/the‐problem‐of‐life.pdf 33. Genetic Algorithms and Artificial Life (1993) (Make Corrections) (36 citations) Melanie Mitchell, Stephanie Forrest. Artificial Life Abstract Genetic algorithms are computational models of evolution that play a central role in many artificial‐life models. We review the history and current scope of research on genetic algorithms in artificial life, using illustrative examples in which the genetic algorithm is used to study how learning and evolution interact, and to model ecosystems, immune system, cognitive systems, and social systems.
Mitchell, M. and S. Forrest (1993). Genetic Algorithms and Artificial Life. Santa Fe Institute. Working paper 93‐11‐072. http://citeseer.ist.psu.edu/mitchell93genetic.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/1481/http:zSzzSzwww.santafe.eduzSz~ mmzSzGA.Alife.pdf/mitchell93genetic.pdf
34. Four Puzzles about Life (1997) (Make Corrections) (3 citations) Mark A. Bedau Reed College, 3203 SE Woodstock Blvd., Portland OR 97202, USA. Artificial Life Abstract This paper proposes that theories of life should be evaluated not by whether they provide necessary and sufficient conditions for our current preconceptions about life but by how well they explain living phenomena and how satisfactorily they resolve salient puzzles about life.
Bedau, M. A. 1997. Four puzzles about life. Lecture presented at a conference on the Philosophy of Artificial Life, PAL97, Christ Church College, Oxford University, March 1997. http://citeseer.ist.psu.edu/article/bedau97four.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/5678/http:zSzzSzwww.inet.gda.plzSzaiz Szftp.cogs.susx.ac.ukzSzpubzSzecal97zSzonlinezSzF129.pdf/bedau97four.pdf 35. The Nature Mark A. Bedau
of
Life
(1996) (Make
Corrections) (9 citations)
Abstract This paper that supple adaptation defines life at its most general. There are plenty of puzzles about the concept of life. The concrete objects ready to hand are usually easily classified as living or non‐living. Fish and ants are alive while candles, crystals and clouds are not. Yet many things are genuinely puzzling to classify as living or not. Viruses are one borderline case, biochemical soups of evolving RNA strings in molecular genetics laboratories are another.
Bedau, M. A. 1996. The nature of life. In M. Boden, (Ed.), The Philosophy of Artificial Life (pp. 332‐‐357). New York: Oxford University Press. http://citeseer.ist.psu.edu/bedau96nature.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/13754/http:zSzzSzweb.reed.eduzSzacad emiczSzdepartmentszSzphilosophyzSzfacultyzSzbedauzSzpszSzoxford.pdf/bedau96na ture.pdf 36. On the Morality of Artificial Agents (2004) (Make Corrections) (1 citation) Luciano Floridi, J. W. Sanders Abstract Artificial agents, particularly those in Cyberspace, extend the class of entities that can be involved in a moral situation. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil).
Floridi, L. and Sanders, J. W. "On the Morality of Artificial Agents", Minds and Machines, 2004, 14.3, pp. 349‐379 . http://citeseer.ist.psu.edu/floridi04morality.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/25718/http:zSzzSzwww.wolfson.ox.ac.u kzSz~floridizSzpdfzSzmaa.pdf/floridi04morality.pdf 37. Nietzsche, God Greg Restall
And
The
Good
Life (Make
Corrections)
Abstract This paper is not only to give a short introduction to what Nietzsche has to say about Christian faith, but also to examine what an appropriate response for believers might be. This then has consequences for what we take the task of `Christian Philosophy' to be.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/14470/ftp:zSzzSzwww.phil.mq.edu.auzS zpubzSzgrestallzSznggl.pdf/nietzsche‐god‐and‐the.pdf 38. Artificial Evil and the Foundation of Computer Ethics (2001) (Make Corrections) (2 citations) Luciano Floridi, J W Sanders. Ethics and Information Technology Abstract Moral reasoning traditionally distinguishes two types of evil: moral (ME) and natural (NE). The standard view is that ME is the product of human agency and so includes phenomena such as war, torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE.
L. Floridi and J. W. Sanders, Artificial evil and the foundation of computer ethics. Ethics and Information Technology, 3(1):55‐‐66, 2001. Preprint from http://www.wolfson.ox.ac.uk/ floridi/papers.htm http://citeseer.ist.psu.edu/floridi01artificial.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/22299/http:zSzzSzwww.wolfson.ox.ac.u kzSz~floridizSzpdfzSzae.pdf/floridi01artificial.pdf 39. Computational Anthony Aaby Abstract
Ethics
(2005) (Make
Corrections)
Competition for and consumption of resources are at the core of ethical issues. Solutions to these problems have been at the core of both operating system design and Internet algorithms. The solutions are traditionally integrated into the software. However, the emergence of intelligent autonomous agents such a bots and spiders which compete with human users for resources on the Internet have introduced unpredictable and uncontrollable elements into the environment.
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/136/http:zSzzSzwww.cs.wwc.eduzSz~a abyanzSzArticleszSzCEthics.pdf/aaby05computational.pdf 40. The Philosophical Foundations of Software Engineering (2004) (Make Corrections) Anthony A. Aaby Abstract The relationship between mathematical logic, theory of computation, philosophy, software quality characteristics, scientific theories, and software design.
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/136/http:zSzzSzwww.cs.wwc.eduzSz~a abyanzSzArticleszSzSE.pdf/aaby04philosophical.pdf 41. SCL: An Artificial Chemistry in Swarm (1997) (Make Corrections) (1 citation) Barry McMullin Abstract This report describes the SCL (v0.04) system. This is an implementation of an artificial chemistry, using the Swarm 1 simulation system. This chemistry is qualitatively based on the system first described in Varela, Maturana & Uribe (1974). This involves three distinct chemical species: Substrate, Catalyst and Link, hence SCL. It was designed with a view to generating simple phenomena of autopoietic organisation.
Barry McMullin. SCL: An artificial chemistry in Swarm. Working Paper 97‐01‐002, Santa Fe Institute, Santa Fe, NM 87501, USA, January 1997. http://www.santafe.edu/sfi/publications/ Working‐Papers/97‐01‐002/ http://citeseer.ist.psu.edu/mcmullin97scl.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/4160/http:zSzzSzwww.inet.gda.plzSzaiz Szwww.santafe.eduzSzsfizSzpublicationszSzWorking‐PaperszSz97‐01‐ 002zSzbmcm9702.pdf/mcmullin97scl.pdf
42. The Artificial Cytoskeleton for Lifetime Adaptation of Morphology (2004) (Make Corrections) (1 citation) Katie Bentley, Chris Clack Abstract The Artificial Cytoskeleton (AC) is introduced as a new model for generating adaptive growth of an artificial cell's morphology throughout its lifetime in response to environmental cues. The AC utilizes swarm and cellular automata techniques. It is closely modelled on the eukaryotic cytoskeleton which is responsible for giving the cell dynamic structure and function.
Bentley, K., Clack, C.: The Artificial Cytoskeleton For Lifetime Adaptation of Morphology. In: Bedau, M. et al (eds.): Workshop Proc. of the 9th Int. Conf. on the Simulation and Synthesis of Living Systems (2004) 13‐‐16 http://citeseer.ist.psu.edu/bentley04artificial.html PDF http://citeseer.ist.psu.edu/cache/papers/cs2/184/http:zSzzSzwww.cs.ucl.ac.ukzSzst affzSzK.BentleyzSzAlife9.pdf/bentley04artificial.pdf 43. Creating High‐level Components with a Generative Representation for Body‐ Brain Evolution (2002) (Make Corrections) (10 citations) Gregory S. Hornby, Jordan B. Pollack Abstract One of the main limitations of scalability in body‐brain evolution systems is the representation chosen for encoding creatures. This paper de nes a class of representations called generative representations, which are identi ed by their ability to reuse elements of the genotype in the translation to the phenotype. This paper presents an example of a generative representation for the concurrent evolution of the morphology and neural controller of simulated robots.
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/656/http:zSzzSzdemo.cs.brandeis.eduz SzpaperszSzhornby_alife02.pdf/hornby02creating.pdf 44. How Artificial Ontogenies Can Retard Corrections) (1 citation) Shivakumar Viswanathan, Jordan Pollack
Evolution
(2005) (Make
Abstract Recently there has been much interest in the role of indirect genetic encodings as a means to achieve increased evolvability. From this perspective, artificial ontogenies have largely been seen as a vehicle to relate the indirect encodings to complex phenotypes. However, the introduction of a development phase does not come without other consequences.
S. Viswanathan. How artificial ontogenies can retard evolution. In H.‐G. Beyer et al., editors, Proceedings of the 2005. http://citeseer.ist.psu.edu/viswanathan05how.html PDF http://citeseer.ist.psu.edu/cache/papers/cs2/655/http:zSzzSzdemo.cs.brandeis.eduz SzpaperszSzshiva_seeds05.pdf/viswanathan05how.pdf 45. Artificial Life Techniques For Generating Controllers For Physically Modelled Characters (2000) (Make Corrections) Tim Taylor Abstract The realistic physical modelling of characters in games and virtual worlds is becoming a viable alternative to more traditional animation techniques. Physical modelling can enhance realism and allow users to interact with the world much more freely. However, designing controllers to move physically modelled characters (e.g. to make a human character walk) is generally a difficult task.
http://citeseer.ist.psu.edu/cache/papers/cs/25919/http:zSzzSzwww.dai.ed.ac.ukzSz homeszSztimtzSzresearchzSz..zSzpaperszSztaylor‐ gameon2000.pdf/taylor00artificial.pdf 46. Some Representational and Ecological Aspects of Evolvability (2000) (Make Corrections) Tim Taylor Abstract: In providing a drive for evolvability has been neglected; even if a system has the capacity for high evolvability, it will not realise this capacity if the appropriate selection pressures are absent.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/21211/http:zSzzSzcomputing.tay.ac.ukz SztimtaylorzSzresearchzSz..zSzpaperszSzevolvability‐timt‐wkshp‐ final.pdf/taylor00some.pdf 47. Grounding and the Entailment Structure in Robots and Artificial Life (1995) (Make Corrections) (6 citations) Erich Prem. European Conference on Artificial Life Abstract This paper is concerned with foundations of ALife and its methodology. A brief look into the research program of ALife serves to clarify its goals, methods and subfields. It is argued that the field of animat research within ALife follows a program which is considerably different from the rest of ALife
endeavours. The simulation ‐‐ non‐simulation debate in behavior based robotics is revisited in the light of ALife criticism and Simon's characterization of the sciences of the artificial.
Prem E. 1995. Grounding and the Entailment Structure in Robots and Artificial Life, in Moran F., et al.(eds.), Advances in Artificial Life. Berlin: Springer, pp. 39‐‐51. http://citeseer.ist.psu.edu/prem95grounding.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/5678/http:zSzzSzwww.inet.gda.plzSzaiz Szftp.ai.univie.ac.atzSzpaperszSzoefai‐tr‐95‐08.pdf/prem95grounding.pdf 48. Machine Epistemology Jörg Wellner
for
Artificial
Life (Make
Corrections)
Abstract This paper is an attempt to explain Machine Epistemology for ALife
PDF http://citeseer.ist.psu.edu/cache/papers/cs/12227/http:zSzzSzwww.tu‐ chemnitz.dezSz~wjozSzgwal.pdf/machine‐epistemology‐for‐artificial.pdf 49. Why are there so few biologists here?" Artificial Life as a theoretical biology of artistry (Make Corrections) Lars Risan Abstract This paper was raised at the final discussion at the Simulation of Adaptive Behavior `94 (SAB 94) conference.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/5678/http:zSzzSzwww.inet.gda.plzSzaiz Szftp.cogs.susx.ac.ukzSzpubzSzecal97zSzonlinezSzF036.pdf/why‐are‐there‐so.pdf 50. Prospects for Open‐Ended Evolution in Artificial Life (2001) (Make Corrections) Russell K. Standish Abstract Of all the issues discussed at Alife VII: Looking Forward, Looking Backward, the issue of whether it was possible to create an artificial life system that exhibits open‐ended evolution of novelty is by far the biggest. Of the 14 open problems settled on as a result of debate at the conference, some 6 are directly, or indirectly related to this issue.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/25826/http:zSzzSzparallel.hpc.unsw.ed u.auzSzrkszSzdocszSzpszSzarob.pdf/standish01prospects.pdf 51. Tierra's missing neutrality: case solved (Make Corrections) Russell K. Standish School of Mathematics, University of New South... Abstract The concept of neutral evolutionary networks being a significant factor in evolutionary dynamics was first proposed by Huynen et al. about 7 years ago. In one sense, the principle is easy to state ‐‐‐ because most mutations to an organism are deleterious, one would expect that neutral mutations that don't affect the phenotype will have disproportionately greater representation amongst successor organisms than one would expect if each mutation was equally likely.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/31150/http:zSzzSzparallel.hpc.unsw.ed u.auzSzrkszSzdocszSzpszSzalife9.pdf/tierra‐s‐missing‐neutrality.pdf 52. Cognition's Coming Home: the Reunion of Life and Mind (1997) (Make Corrections) (4 citations) Michael Wheeler Abstract I draw a distinction between orthodox cognitive science and biological cognitive science. The former tends to ignore biological considerations whilst the latter holds that life and mind share a common set of organizational principles. The suggestion here is that artificial life (A‐Life) is (potentially) the intellectual engine of the latter. The goal then becomes to map out the conceptual profile of that A‐Life‐ driven cognitive science.
Wheeler, M. (1997). Cognition's coming home: The reunion of life and mind. In Husbands, P. and Harvey, I., editors, Proceedings of the Fourth European Conference on Artificial Life, pages 10‐‐19, Cambridge, MA. MIT Press. http://citeseer.ist.psu.edu/wheeler97cognitions.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/2521/ftp:zSzzSzftp.cogs.susx.ac.ukzSzpu bzSzecal97zSzonlinezSzF035.pdf/wheeler97cognitions.pdf 53. Evaluating Artificial Life and Artificial Organisms (Make Corrections) Brian L. Keeley Experimental Philosophy Laboratory, Department of Philosophy, ... Abstract
It is often heard in Artificial Life (A‐Life) circles that contemporary biology studies life‐as‐we‐know‐it (an Earth based, carbon chain phenomenon), whereas A‐Life takes as its domain of study life‐as‐it‐could‐be. But lacking a clear definition of "life " the question arises: how would we recognize life‐as‐it‐could‐be, if we managed to create it?
PDF http://citeseer.ist.psu.edu/cache/papers/cs/2520/http:zSzzSzartsci.wustl.eduzSz~bk eeleyzSzworkzSzpubszSzevaluating_alifezSzBK_ALV.pdf/evaluating‐artificial‐life‐ and.pdf 54. The Problem Rich Cameron
of
Life's
Definition (Make
Corrections)
Abstract Building on our previous research, which deals with learning autonomous robots evolving in unknown environments, we investigate various categorization issues and discuss how models drawn from catastrophe theory may help to solve the symbol grounding problem for such robots. Key words: robot, knowledge modeling, catastrophe theory. 1 Introduction In previous work [6, 7, 8, 9], we have focused on the learning of control laws for input/output systems such as robots.
D. Luzeaux, "Catastrophes as a way to build up knowledge for learning robots," in 16th IMACS World Congress, (Lausanne, Switzerland), 2000. http://citeseer.ist.psu.edu/luzeaux00catastrophes.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/16301/http:zSzzSzwww.etca.frzSzCTAzS zgipzSzPubliszSzLuzeauxzSzimacs00.pdf/luzeaux00catastrophes.pdf 55. How Economists Can Get Alife (1997) (Make Corrections) (17 citations) Leigh Tesfatsion Abstract This paper presents a summary overview of the fast‐developing field of artificial life, stressing aspects especially relevant for the study of decentralized market economies. In particular, a recently developed trade network game (TNG) is used to illustrate how the basic artificial life paradigm might be specialized to economics. The TNG traders choose and refuse trade partners on the basis of continually updated expected utility and evolve their trade behavior over time.
Tesfatsion, L., How economists can get alife, pp. 533‐‐564 in W. Brian Arthur, Steven Durlauf, and David Lane (eds.), The Economy as an Evolving Complex System, II , Santa Fe Institute Studies in the Sciences of Complexity, Proceedings Volume XXVII, Addison‐ Wesley, 1997. http://citeseer.ist.psu.edu/tesfatsion97how.html PDF
http://citeseer.ist.psu.edu/cache/papers/cs/5561/http:zSzzSzwww.ai.mit.eduzSzcou rseszSz6.836zSzspring98zSztesfatsion.pdf/tesfatsion97how.pdf 56. BURN: A Simulation of Forest Fire Propagation (1994) (Make Corrections) Marshall S. Veach, Paul Coddington, Geoffrey C. Fox Abstract A project is described which designed, implemented and evaluated a simulation of forest fire propagation as a cellular automaton in a parallel environment. Fire models developed by Richard Rothermel were used as the basis for propagation behavior. Furthermore, the simulation was developed to support a variety of applications including fire propagation prediction and the evaluation of fire fighting effectiveness. 1 Artificial Life, Cellular Automata & Ecological Modeling.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/5642/ftp:zSzzSzftp.npac.syr.eduzSzpubz SzprojectszSzreuzSzreu94zSzmveachzSzpaperzSzpaper.pdf/veach94burn.pdf 57. Perceptual Modeling for Behavioral Animation of Fishes (1994) (Make Corrections) (8 citations) Xiaoyuan Tu, Demetri Terzopoulos Abstract The realistic animation of animal behavior by autonomous animate agents requires that the agents able to perceive their virtual worlds. We have created a virtual marine world inhabited by artificial fishes which can swim hydrodynamically in simulated water through the motor control of internal muscles. Artificial fishes exploit a rudimentary model of fish perception. Complex individual and group behaviors, including target tracking, obstacle avoidance, feeding, preying, schooling, and mating.
X. Tu and D. Terzopoulos. Perceptual modeling for behavioral animation of fishes. In J. Chen et al., editor, Proc. Second Pacific Conference on Computer Graphics, pages 185‐‐ 200, 1994. http://citeseer.ist.psu.edu/tu94perceptual.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/1306/http:zSzzSzwww.dgp.toronto.eduzSz peoplezSztuzSz.zSzpaperszSzpg94.pdf/tu94perceptual.pdf 58. Artificial Animals in Realistic Virtual Worlds (1996) (Make Corrections) Demetri Terzopoulos Abstract This paper describes a virtual marine ecosystem inhabited by realistic artificial life that emulates the appearance, movement, and behavior of real fishes. Each artificial fish is an autonomous agent in a simulated physical world. It has (i) a three‐dimensional body with internal muscle actuators and
functional fins, which deforms and locomotes in accordance with biomechanic and hydrodynamic principles, (ii) sensors, including eyes that can image the environment.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/22464/ftp:zSzzSzftp.cs.toronto.eduzSzp ubzSzdtzSzinfo‐tech96.pdf/terzopoulos96artificial.pdf 59. Topics in Computer Animation and Some Relevant Papers (1997) (Make Corrections) Jane Wilhelms Abstract C151‐‐C158, September 1997. [WFB87] Andrew Witkin, Kurt Fleischer, and Alan H. Barr. Energy constraints on parameterized models. SIGGRAPH '87 Conference Proceedings, 21(4):225‐‐232, (Anaheim, CA, July, 1987). [WG97] Jane Wilhelms and Allen Van Gelder. Anatomically based modeling. In Computer Graphics, pages 173‐‐180, Los Angeles, Ca., August 1997. ACM Siggraph Conference Proceedings. [WH91] Jakub Wejchert and David Haumann. Animation aerodynamics. Computer Graphics
PDF http://citeseer.ist.psu.edu/cache/papers/cs/2939/http:zSzzSzwww.cse.ucsc.eduzSz~ wilhelmszSz262zSzpapers.pdf/wilhelms97topics.pdf 60. Animat Vision: Active Vision in Artificial Animals (1997) (Make Corrections) (24 citations) Demetri Terzopoulos, Tamer F. Rabie. ICCV Abstract We propose and demonstrate a new paradigm for active vision research that draws upon recent advances in the fields of artificial life and computer graphics. A software alternative to the prevailing hardware vision mindset, animat vision prescribes artificial animals, or animats, situated in physics‐ based virtual worlds as autonomous virtual robots with active perception systems. To be operative in its world, an animat must autonomously control its eyes and muscle‐actuated body.
D. Terzopoulos and T. Rabie. Animat Vision: Active Vision in Artificial Animals. In Int. Conf. on Computer Vision, pp. 801‐808, 1995. http://citeseer.ist.psu.edu/article/terzopoulos97animat.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/225/http:zSzzSzwww.cs.toronto.eduzSz~d tzSzpaperszSzvidere97zSzvidere97.pdf/terzopoulos97animat.pdf
61. Making Them Behave: Cognitive Models for Computer Animation (1998) (Make Corrections) (19 citations) John David Funge Abstract Making Them Behave Cognitive Models for Computer Animation John David Funge Doctor of Philosophy Graduate Department of Computer Science University of Toronto 1998 For applications in computer game development and character animation, recent work in behavioral animation has taken impressive steps toward autonomous, self‐animating characters. It remains difficult, however, to direct autonomous characters to perform specific tasks.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/11560/http:zSzzSzwww.cs.toronto.eduzSz ~fungezSzpublicationszSz.zSzfungeSc.pdf/funge98making.pdf 62. Representing Knowledge within the Situation Calculus using Interval‐valued Epistemic Fluents (1999) (Make Corrections) (5 citations) John Funge Abstract The ability of interval arithmetic to provide a finite (and succinct) way to represent uncertainty about a large, possibly uncountable, set of alternatives turns out to be useful in building "intelligent" autonomous agents. In particular, consider the two important issues of reasoning and sensing in intelligent control for autonomous agents. Developing a principled way to combine the two raises complicated issues in knowledge representation.
J. Funge. Representing knowledge within the situation calculus using intervalvalued epistemic fluents. Journal of Reliable Computing, 5(1), 1999. http://citeseer.ist.psu.edu/funge99representing.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/16556/http:zSzzSzwww.dgp.toronto.ed uzSz~fungezSz.zSzpdfzSzreliable99.pdf/funge99representing.pdf 63. Using Artificial Physics to Corrections) (17 citations) William M. Spears, Diana F. Gordon
Control
Agents
(1999) (Make
Abstract We introduce a novel framework called "artificial physics", which provides distributed control of large collections of agents. The agents react to artificial forces that are motivated by natural physical laws. This framework provides an effective mechanism for achieving self‐assembly, fault‐tolerance, and self‐ repair. Examples are shown for various regular geometric configurations of agents.
Spears, W., and Gordon, D. 1999. Using artificial physics to control agents. In IEEE International Conference on Information, Intelligence, and Systems. http://citeseer.ist.psu.edu/spears99using.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/22644/http:zSzzSzwww.aic.nrl.navy.mil zSz~spearszSzpaperszSziciis99.pdf/spears99using.pdf 64. The Evolution of Animal Comunication Systems: (1998) (Make Corrections) Jason Noble Abstract This paper but all of the work actually presented in the chapter is my own. Chapter 7 is based on a paper published in the Proceedings of the Sixth Conference on Artificial Life (Noble, 1998b) and presented at the Second International Conference on the Evolution of Language (Noble, 1998a); an extended version of the work is currently in press in the journal Adaptive Behavior.
PDF http://citeseer.ist.psu.edu/cache/papers/cs2/82/http:zSzzSzwww.comp.leeds.ac.ukz SzjasonnzSzResearchzSzThesiszSzthesis.pdf/noble98evolution.pdf 65. Virtual Reality: Consciousness Really Explained (1995) (Make Corrections) Jerome Iglowitz Abstract I argue that the evolutionary rationale for the brains of organisms was not representation nor reactive parallelism as is generally proposed, but was specifically an internal operational organization of blind biologic process instead. I propose that our cognitive objects are deep metaphors of primitive biological response rather than informational referents to environment.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/19057/http:zSzzSzwww.foothill.netzSz~ jerryizSzCOMPILED9‐2‐00.PDF/iglowitz95virtual.pdf 66. Sexual Signalling in an Artificial Population: When Does the Handicap Principle Work? (1999) (Make Corrections) (1 citation) Jason Noble. European Conference on Artificial Life Abstract Males may use sexual displays to signal their quality to females; the handicap principle provides a mechanism that could enforce honesty in such cases. Iwasa et al. [1] model the signalling of inherited male quality, and distinguish between three variants of the handicap principle: pure epistasis, conditional, and revealing. They argue that only the second and third will work. An evolutionary simulation is presented in which all three variants function under certain conditions.
Noble, J., (1999). Sexual signalling in an artificial population: when does the handicap principle work? In: Proceedings of the 5 European Conference on Artificial Life, Springer‐Verlag, pp. 644‐‐‐653. http://citeseer.ist.psu.edu/noble99sexual.html More PDF http://citeseer.ist.psu.edu/cache/papers/cs/15838/http:zSzzSzwww‐abc.mpib‐ berlin.mpg.dezSzuserszSznoblezSzResearchzSzSexualzSzecal99.pdf/noble99sexual.pd f 67. Cooperation, Conflict and the Evolution of Communication (Make Corrections) Jason Noble Abstract This paper presents a general model that covers signalling with and without conflicts of interest between signallers and receivers. Krebs and Dawkins (1984) argued that a conflict of interests will lead to an evolutionary arms race between manipulative signallers and sceptical receivers, resulting in ever more costly signals; whereas common interests will lead to cheap signals or "conspiratorial whispers".
PDF http://citeseer.ist.psu.edu/cache/papers/cs/15838/http:zSzzSzwww‐abc.mpib‐ berlin.mpg.dezSzuserszSznoblezSzResearchzSzCoopCompzSzab.pdf/cooperation‐ conflict‐and‐the.pdf 68. Concepts of Cooperation in Artificial Corrections) (1 citation) Harold W. Thimbleby, Ian H. Witten, David J. Pullinger
Life
(1998) (Make
Abstract We have built some simple, but useful, cooperative Artificial Life agents. Based on this experience and by contrasting our work with computer viruses, we argue that Artificial Life (the simulation of life including evolution) can only remain reliably and indefinitely cooperative if it adheres to explicitly‐ specified social conventions.
H.W. Thimbleby, I.H. Witten, D.J. Pullinger, Concepts of Cooperation in Artificial Life, IEEE Transactions on Systems, Man and Cybernetics, 25, no 7 (1995). http://citeseer.ist.psu.edu/thimbleby98concepts.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/30420/http:zSzzSzwww.uclic.ucl.ac.ukz SzharoldzSzsrfzSzlife.pdf/thimbleby98concepts.pdf
69. The Mathematics of Nepotism: (Make Corrections) A Review of Foundations of Social Evolution by Steven A. Frank Jason Noble... Abstract Ok is about the proper measures of success or fitness needed to study social evolution. It is intended as both a practical guide to constructing mathematical models, and as a summary of the kin selection literature. The book also features original models and arguments. Frank focuses on three evolutionary currencies: marginal value, reproductive value, and inclusive fitness. The first two of these have familiar economic interpretations. PDF http://citeseer.ist.psu.edu/cache/papers/cs/27770/http:zSzzSzwww.comp.leeds.ac. ukzSzjasonnzSzResearchzSzMethodzSzsocEvoReview.pdf/the‐mathematics‐of‐ nepotism.pdf 70. Artificial Life: Discipline or Method? (1999) (Make Corrections) Jason Noble, Seth Bullock, Ezequiel A. Di Paolo Abstract Genetic algorithms and animat‐style simulations to look at existing problems. Typically the problems come from within biology. The work of Kitano and his colleagues (e.g., 1997) on morphogenesis in Drosophila is one example. We see this work as exemplifying the idea of AL as a method, or a collection of methods, that could (at least in theory) be put to use by investigators in many different fields.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/12751/http:zSzzSzwww.cogs.susx.ac.uk zSzuserszSzezequielzSzaldm.pdf/noble99artificial.pdf 71. Models of Anders Sandberg
Development
(2000) (Make
Corrections)
Abstract The central question of development is: how does structure emerge from a structureless state without an external organizing force? The answer seems to be that self‐organising processes are able to produce complex structures from simple initial states. In biological systems a major factor appears to be di usion of chemical factors guiding growth or differentiation.
PDF
http://citeseer.ist.psu.edu/cache/papers/cs/15161/http:zSzzSzwww.nada.kth.sezSz~ asazSzWorkzSz..zSzTextszSzmorph.pdf/sandberg00models.pdf
72. Creativity in Evolution: Individuals, Interactions and Environments (Make Corrections) Tim Taylor Abstract This chapter addresses the nature of open‐ended evolutionary processes, and the related, but more subtle, issue of how fundamental novelty (i.e. creativity) can arise in such processes. A number of existing artificial evolutionary systems, such as Tierra (Ray, 1991), are analysed in this context, but it is found that the theoretical grounding upon which they are based does not usually consider all of the relevant issues for creative evolution.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/14594/http:zSzzSzwww.dai.ed.ac.ukzSz daidbzSzhomeszSztimtzSzpaperszSzces‐book‐sub.pdf/creativity‐in‐evolution‐ individuals.pdf 73. Artificial Chemistry: Computational Studies on the Emergence of Self‐ Reproducing Units (2001) (Make Corrections) (1 citation) Naoaki ONO, Takashi IKEGAMI. Lecture Notes in Computer Science Abstract Acquisition of self‐maintenance of cell membranes is an essential step to evolve from molecular to cellular reproduction. In this report, we present a model of artificial chemistry that simulates metabolic reactions, di#usion and repulsion of abstract chemicals in a two‐dimensional space to realize the organization of proto‐cell structures. It demonstrates that proto‐cell structures that maintain and reproduce themselves autonomously emerge from a non‐organized initial configuration.
Ono, N. Ph.D. thesis, Artificial Chemistry: Computational Studies on the Emergence of Self‐Reproducing Units, Univ. of Tokyo, (March 2001). http://citeseer.ist.psu.edu/ono01artificial.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/28126/http:zSzzSzsacral.c.u‐ tokyo.ac.jpzSz~nonozSzbook2zSzpublicationszSzecal2001.pdf/ono01artificial.pdf 74. Artificial Intelligence and Scientific Creativity (1999) (Make Corrections) Simon Colton, Graham Steel Abstract Introduction There has been much recent success for AI systems undertaking creative tasks in scientific domains such as astronomy, biology, medicine, chemistry, physics and mathematics. In many scientific domains, we can build on the wealth of philosophical and computational studies into creative aspects of human intelligence, and use the abstract nature of the data to derive specialist algorithms for discovery.
PDF
http://citeseer.ist.psu.edu/cache/papers/cs/23053/http:zSzzSzwww.dai.ed.ac.ukzSz daidbzSzpeoplezSzhomeszSzsimoncozSzpaperszSzAISBQ99.pdf/colton99artificial.pdf 75. Open Problems in Artificial Life (2000) (Make Corrections) (7 citations) Mark A. Bedau, John S. McCaskill, Norman H. Packard, Steen Rasmussen, Chris Adami, David G. Green, Takashi Ikegami, Kunihiko Kaneko, Thomas S. Ray. ARTLIFE: Artificial Life Abstract This paper lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained and, where deemed helpful, some promising paths to its solution are indicated. Introduction At the dawn of the last century, Hilbert proposed a set of open mathematical problems. They proved to be an extraordinarily effective guideline for mathematical research in the following century.
Bedau, M., McCaskill, J. S., Packard, N., Rasmussen, S., Adami, C., Green, D. G., Ikegami, T., Kaneko, K., and Ray, T. (2000). Open problems in artificial life. Artificial Life 6, 363‐‐ 376. http://citeseer.ist.psu.edu/bedau00open.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/17336/http:zSzzSzwww.reed.eduzSz~mab zSzpaperszSzquestions.pdf/bedau00open.pdf 76. Machine Discovery in Corrections) (4 citations) Raúl Valdés‐Pérez
Chemistry:
New
Results
(1995) (Make
Abstract Earlier we proposed an idea for conjecturing unseen entities in science, and described its application within MECHEM to the chemistry task of inferring the mechanism of a chemical reaction based on experimental evidence. However, the program was a prototype, and lacked several capabilities that rendered it incompetent on current science.
Valdes‐Perez, R.E. (1995). Machine Discovery in Chemistry: New Results. Arti cial Intelligence 74(1), 191‐201. http://citeseer.ist.psu.edu/512636.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/25319/http:zSzzSzwww.cs.cmu.eduzSzafsz SzcszSzuserzSzvaldeszSzMosaiczSzPostscriptzSzaij95.pdf/machine‐discovery‐in‐ chemistry.pdf 77. Open Problems in Artificial Life (2001) (Make Corrections) (7 citations) Mark A. Bedau, John S. McCaskill, Norman H. Packard, Steen Rasmussen, Chris
Adami, David G. Green, Takashi Ikegami, Kunihiko Kaneko, Thomas S. Ray. Artificial Life Abstract This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.
Bedau, M., McCaskill, J. S., Packard, N., Rasmussen, S., Adami, C., Green, D. G., Ikegami, T., Kaneko, K., and Ray, T. (2000). Open problems in artificial life. Artificial Life 6, 363‐‐ 376. http://citeseer.ist.psu.edu/article/bedau01open.html PDF http://citeseer.ist.psu.edu/cache/papers/cs/31792/http:zSzzSzmitpress.mit.eduzSzjour nalszSzARTLzSzBedau.pdf/bedau01open.pdf 78. The Scientific and Philosophical Scope of Artificial Life (Make Corrections) Mark Bedau Abstract The new interdisciplinary science of artificial life has had a connection with the arts from its inception. This paper provides an overview of artificial life, reviews its key scientific challenges, and discusses its philosophical implications. It ends with a few words about the implications of artificial life for the arts. Artificial life is a young interdisciplinary collection of research activities aimed at understanding the fundamental behavior of life‐like systems.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/28596/http:zSzzSzwww.reed.eduzSz~mab zSzpaperszSzleonardo.pdf/the‐scientific‐and‐philosophical.pdf 79. A Comparison of Evolutionary Activity in Artificial Evolving Systems and in the Biosphere (1997) (Make Corrections) (10 citations) Mark A. Bedau, Emile Snyder, C. Titus Brown, Norman H. Packard Abstract Bedau and Packard [7] devised an approach to quantifying the adaptive phenomena in artificial systems. We use this approach to define two statistics: cumulative evolutionary activity and mean cumulative evolutionary activity. Then we measure the dynamics of cumulative evolutionary activity, mean cumulative evolutionary activity and diversity, on an evolutionary time scale, in two artificial systems and in the biosphere as reflected in the fossil record.
Bedau, Mark A., Emile Snyder, C. Titus Brown, Norman Packard, "A Comparison of Evolutionary Activity in Artificial Evolving Systems and in the Biosphere", Proceedings of the Fourth European Conference on Artificial Life, Phil Husbands and Inman Harvey,
eds., MIT Press/Bradford http://citeseer.ist.psu.edu/bedau97comparison.html
Books
(1997).
PDF http://citeseer.ist.psu.edu/cache/papers/cs/2522/http:zSzzSzwww.santafe.eduzSzsfizS zpublicationszSzWorking‐PaperszSz98‐03‐024.pdf/bedau97comparison.pdf 80. Music Generation through Cellular Automata: How to Give Life to Strange Creatures (2000) (Make Corrections) Eleonora Bilotta, Pietro Pantano, Valerio Talarico Abstract Cellular Automata (CA), like every other dynamical system, can be used to generate music. Starting from any initial state and applying to CA simple transition rules, such models are able to produce numerical sequences that can be successively associated to physical parameters. This approach is interesting because, maintaining fixed the set of rules and varying the initial data, many different, though correlated, numerical sequences can be originated, which in turn can be translated into music.
PDF http://citeseer.ist.psu.edu/cache/papers/cs/20491/http:zSzzSzuni.abramo.itzSzserverz SzserverzSzCubo20zSzpresentazSzpeoplezSzBilozSz..zSz..zSz..zSzRicercazSzpaperszSz20 00zSzmilano.pdf/music‐generation‐through‐cellular.pdf
