View Full Version : Artificial Life vs. Artificial Intelligence: Conference

11-11-1993, 01:36 PM
From: Arantza Etxeberria
Subject: Artificial Life Workshop Announcement
Date: Mon, 18 Oct 93 10:48:42 BST

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

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.

* 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
E. Mail: biziart@si.ehu.es
Fax: 34 43 311056
Phone: 34 43 310600 (extension 221)
34 43 218000 (extension 209)

Stevan Harnad
Laboratoire Cognition et Mouvement
URA CNRS 1166 I.B.H.O.P.
Universite d'Aix Marseille II
13388 Marseille cedex 13, France

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

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

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@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

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]