INTERNATIONAL SCHOOL ON NEURAL NETS <<E.R. CAIANIELLO>>

Fri Jul 23 06:20:06 EDT 1999

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4th Course: Subsymbolic Computation in Artificial Intelligence

ERICE-SICILY: October 24-31, 1999

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MOTIVATIONS

Autonomous intelligent agents that perform complex real world
tasks must be able to build and process rich internal representations
that allow them to effectively draw inferences, make decisions, and,
in general, perform reasoning processes concerning their own tasks.
Within the computational framework of artificial intelligence (AI)
this problem has been faced in different ways. According to the
classical, symbolic approach, internal representations are conceived
in terms of linguistic structures, as expressions of a "language of
thought". Other traditions developed approaches that are less
linguistically oriented, and more biologically and anatomically
motivated. It is the case of neural networks, and of self-organizing
and evolutionary algorithms.

Empirical results concerning natural intelligent systems suggest that
such approaches are not fully incompatible, and that different kinds
of representation may interact. Similarly, it can be argued that the
design of artificial intelligent systems can take advantage from
different kinds of interacting representations, that are suited for
different tasks.

In this perspective, theoretical frameworks and methodological
techniques are needed, that allow to employ together in a principled
way different kinds of representation. In particular, autonomous
agents need to find the meaning for the symbols they use within
their internal processes and in the interaction with the external
world, thus overcoming the well-known symbol grounding problem.

An information processing architecture for autonomous intelligent
agents should exhibit processes that act on suitable intermediate
levels, which are intermediary among sensory data, symbolic level,
and actions. These processes could be defined in terms of
subsymbolic computation paradigms, such as neural networks, self-
organizing, and evolutionary algorithms.

DIRECTOR OF THE COURSE: Salvatore Gaglio
DIRECTOR OF THE SCHOOL: M.I.Jordan - M.Marinaro
DIRECTOR OF THE CENTRE: A. Zichichi
SCIENTIFIC SECRETARIAT:
Edoardo Ardizzone, Antonio Chella, Marcello Frixione

WEB PAGE OF THE COURSE: http://dijkstra.cere.pa.cnr.it/ScuolaErice/

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SPONSORS

+ ASEIT Advanced School on Electronics and Information Technology
+ AI*IA Associazione Italiana per l'Intelligenza Artificiale
(Italian Association for Artificial Intelligence)
+ CERE - CNR CEntro di Studio sulle Reti di Elaboratori
(Center of Study on Computer Networks)
+ CITC Centro Interdipartimentale sulle Tecnologie della Conoscenza
+ Commission of the European Communities
+ IEEE  Neural Network Council
+ IIASS Istituto Internazionale per gli Alti Studi Scientifici
(International Institute for Advanced Scientific Studies)
+ Ministero Italiano della Pubblica Istruzione
(Italian Ministry of Education)
+ MURST Ministero dell'Universita' e della Ricerca Scientifica e
Tecnologica (Italian Ministry of University and Scientific Research)
+ CNR Consiglio Nazionale della Ricerca
(Italian National Research Council)
+ Regione Siciliana (Sicilian Regional Government)
+ SIREN Societa' Italiana Reti Neuroniche (Italian Neural
Networks Society)
+ University of Genoa
+ University of Palermo
+ University of Salermo

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PROGRAM

FOUNDATIONS

Introduction to Artificial Intelligence:  Luigia Carlucci Aiello
(University of Roma, "La Sapienza", Italy)

Neural modelling of higher order cognitive processes: John Taylor
(King's College, London, UK)

Connectionist Models for Data Structures: Marco Gori
(University of Siena, Italy)

Neural Systems Engineering: Igor Aleksander
(Imperial College, London, UK)

ASEIT (Advanced School on Electronics and Information Technology)
OPEN INTERNATIONAL WORKSHOP ON
SUBSYMBOLIC TECHNIQUES AND ALGORITHMS

Peter G=E4rdenfors (Lund University, Sweden)

Igor Aleksander (Imperial College, London, UK))

Teuvo Kohonen (Helsinki University of Technology, Finland)

John Taylor (King's College, London, UK)

Ronald Arkin (Georgia Institute of Technology, USA)

REPRESENTATION

Conceptual Spaces: Peter G=E4rdenfors
(Lund University, Sweden)

Topological Self Organizing Maps: Teuvo Kohonen
(Helsinki University of Technology, Finland)

Symbolic representations:  Luigia Carlucci Aiello
(University of Roma, =ECLa Sapienza=EE, Italy)

VISUAL PERCEPTION

Evolutionary Processes for Artificial Perception:
Giovanni Adorni, Stefano Cagnoni (University of Parma, Italy)

Cognitive Architectures for Artificial Vision:
Antonio Chella (Univ. of Palermo, Italy),
Marcello Frixione (Univ. of Salerno, Italy),
Salvatore Gaglio (Univ. of Palermo, Italy)

Algorithms for Image Analysis: Vito Di Ges=F9
(Univ. of Palermo, Italy)

ACTION

Motion Maps: Pietro Morasso
(University of Genoa, Italy)

Interacting with the External World: Luc Steels
(Free University of Brussels, Belgium)

Reinforcement Learning in Autonomous Robots: Christian Balkenius
(Lund University, Sweden)

Behavior-Based Robotics: Ronald Arkin
(Georgia Institute of Technology, USA)

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APPLICATIONS

Interested candidates should send a letter to the
Director of the Course:

Professor Salvatore GAGLIO
Dipartimento di Ingegneria Automatica e Informatica
Universita' di Palermo
Viale delle Scienze
90128 - PALERMO - ITALY

Tel: ++39.091.238245
Fax: ++39.091.6529124
E-mail: gaglio at unipa.it

They should specify:
1.date and place of birth, together with present nationality;
2.affiliation;
3.address, e-mail address.

Please enclose a letter of recommendation from the group
leader or the Director of the Institute or from a senior scientist.

PLEASE NOTE

Participants must arrive in Erice on October 24,
not later than 5:00 pm.

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