KOGLIST: RE:Artificial Life Workshop

Date: Tue, 16 Nov 1993 12:13:55 -0500 Reply-To: PSYCHE Discussion Forum <PSYCHE-D%NKI.BITNET(a)uga.cc.uga.edu> Sender: PSYCHE Discussion Forum <PSYCHE-D%NKI.BITNET(a)uga.cc.uga.edu> From: PATRICK WILKEN <X91007(a)pitvax.xx.rmit.edu.au> Subject: Artificial Life Workshop X-To: psyche-d(a)NKI.bitnet To: Multiple recipients of list PSYCHE-D <PSYCHE-D%NKI.BITNET(a)uga.cc.uga.edu> ARTIFICIAL LIFE: A BRIDGE TOWARDS A NEW ARTIFICIAL INTELLIGENCE Palacio de Miramar (San Sebastian, Spain) December 10th and 11th, 1993 Workshop organised by the Department of Logic and Philosophy of Science, Faculty of Computer Science & Institute of Logic, Cognition, Language and Information (ILCLI) of the University of the Basque Country (UPV/EHU) Directors: Alvaro Moreno (University of the Basque Country) Francisco Varela (CREA, Paris) This Workshop will be devoted to a discussion of the impact of work on Artifical Life on Artificial Intelligence. Artificial Intelligence (AI) has traditionally attempted to study cognition as an abstract phenomenon using formal tools, that is, as a disembodied process that can be grasped through formal operations, independent of the nature of the system that displays it. Cognition is treated as an abstract representation of reality. After several decades of research in this direction the field has encountered several problems that have taken it to what many consider a "dead end": difficulties in understanding autonomous and situated agencies, in relating to behaviour in a real environment, in studying the nature and evolution of perception, in finding a practical explanation for the operation of most cognitive capacities such as natural language, context dependent action, etc. Artificial Life (AL) has recently emerged as a confluence of very different fields trying to study different kinds of features of living systems using computers as a modelling tool, and, at last, trying to artificially (re)produce a living system (or a population of them) in real or computational media. Examples of such phenomena are prebiotic systems and their evolution, growth and development, self-reproduction, adaptation to an environment, evolution of ecosystems and natural selection, formation of sensory-motor loops, autonomous robots. Thus, AL is having an impact on classic life sciences but also on the conceptual foundations of AI and new methodological ideas in Cognitive Science. The aim of this Workshop is to focus on the last two points and to evaluate the influence of the methodology and concepts appearing in AL for the development of new ideas about cognition that could eventually give birth to a new Artificial Intelligence. Some of the sessions consist of presentations and replies on a specific subject by invited speakers while others will be debates open to all participants in the workshop. MAIN TOPICS: * A review of the problems of FUNCTIONALISM in Cognitive Science and Artificial Life. * Modelling Neural Networks through Genetic Algorithms. * Autonomy and Robotics. * Consequences of the crisis of the representational models of cognition. * Minimal Living System and Minimal Cognitive System * Artificial Life systems as problem solvers * Emergence and evolution in artificial systems SPEAKERS S. Harnad P. Husbands G. Kampis B. Mac Mullin D. Parisi T. Smithers E. Thompson F. Varela Further Information: Alvaro Moreno Apartado 1249 20080 DONOSTIA SPAIN E. Mail: biziart(a)si.ehu.es Fax: 34 43 311056 Phone: 34 43 310600 (extension 221) 34 43 218000 (extension 209) ----------------------------------------------------------------------- LEVELS OF FUNCTIONAL EQUIVALENCE IN REVERSE BIOENGINEERING: THE DARWINIAN TURING TEST FOR ARTIFICIAL LIFE Stevan Harnad Laboratoire Cognition et Mouvement URA CNRS 1166 I.B.H.O.P. Universite d'Aix Marseille II 13388 Marseille cedex 13, France harnad(a)princeton.edu ABSTRACT: Both Artificial Life and Artificial Mind are branches of what Dennett has called "reverse engineering": Ordinary engineering attempts to build systems to meet certain functional specifications; reverse bioengineering attempts to understand how systems that have already been built by the Blind Watchmaker work. Computational modelling (virtual life) can capture the formal principles of life, perhaps predict and explain it completely, but it can no more BE alive than a virtual forest fire can be hot. In itself, a computational model is just an ungrounded symbol system; no matter how closely it matches the properties of what is being modelled, it matches them only formally, with the mediation of an interpretation. Synthetic life is not open to this objection, but it is still an open question how close a functional equivalence is needed in order to capture life. Close enough to fool the Blind Watchmaker is probably close enough, but would that require molecular indistinguishability, and if so, do we really need to go that far? ----------------------------------------------------------------------- Phil Husbands School of Cognitive and Computing Sciences Univesity of Sussex, BRIGHTON BN1 9QH, U.K philh(a)cogs.susx.ac.uk ABSTRACT: We discuss the mothodological foundations for our work on the development of cognitive architectures, on control systems, for situated autonomous agents. We focus on the problems of developing sensory-motor ystems for mobile robots, but we also discuss the applicability of aur approach to the study of biological systems. We argue that, for agents required to exhibit sophisticated ionteractions with their environments, complex sensory-motor processing is necessary, and the design by hand of control systems capable of this is likely to to become a prohibiytively difficult as complexity increases. We propose an automatic design process involving artificial evolution,where the basoc buildig blocks used for evolving cognitive architectures are noise-tolerant dynamical networks. These networks may be recurrent, and should operate in real time. time. The evolution should be incremental, using an extended and modified version of a genetic algorithm. Practical constraints suggest that initial architecture evaluations should be done largely in simulation. To support our claims and proposals, we summarize results from some preliminary simulation experiments where visually guided robots are evolved to operate in simple environments. Significantly, our results demonstrate that robust visually-guided control systems evolve from evaluation fuctions which do not explicitly require monitoring visual input. We outline the difficulties involved in continuing with simulations, and conclude by describing specialized visuo-robotic equipment, designed to eliminate sensors and actuators. ----------------------------------------------------------------------- Barry MacMullin School of Electronic Engineering Dublin City University McMullinB(a)DCU.IE ABSTRACT: I reconsider the status of computationalism (or, in a weak sense, functionalism): the claim that being a realisation of some (as yet unespecified) class of abstract machine is both necessary ans sufficient for having genuine, full-blooded, mentality. This doctrine is now quite widely (though by no means universally) seen as discredited. My position is that, thoug it is undoubtedly an unsatisfactory (perhaps even repugnant) thsis, the arguments against it are still rather weak. In particular, I critically reassess John Searle's infamous Chinise Room Argument, and also some relevant aspects of Karl Popper s theory of the Open Universe. I conclude that the status of computationalism must still be regarded as undecided' and that it may still provide a satisfactory framework for research. ----------------------------------------------------------------------- Domenico Parisi Institute of Psychology National Research Council, Rome e-mail: domenico(a)irmkant.bitnet ABSTRACT: Genetic algorithms are methods of parallel search for optimal solutions to tasks which are inspired by biological evolution and are based on selective reproductiomn and the addition of variiation through mutations or crossover. As models of real biological and behevioral phenomena, however, genetic algorithms suffer from many limitations. Some of these limitations are discussed under the rubrics of (a) environment, (b) variation, and (c) fitness, and ways are suggested to overcome them. Various simulations using genetic algoritms and neural networks are briefly described which incorporate a more biologically realistic notion of evolution. ----------------------------------------------------------------------- Tim Smithers Facultad de Informatica Apartado 649 20080 San Sebastian smithers(a)si.ehu.es ABSTRACT: Traditianally autonomous systems research has been a domain of Artificial Intelligence. We argue that, as a consequence, it has been heavily influenced, often tacitly, by folk psychological notions. We believe that much of the widely acknowledged failure of this research to produce reliable and robust artificial autonomous systems can be apportioned to its use and dependence upon forlk psychological constructs. As an alternative we propose taking seriously the Eliminativce Materialism of Paul Chuchland In this paper we present our reasons for adopting this radical alternative approach and briefly describe the bottom-up methodology that goes with it. We illustrate the discussion with examples form our work on autonomous systems. [Rest of abstracts not yet available]