Download here the .zip file (2.13 MB) with all the contributions to the workshop
:: scope and objectives
Social learning refers to the process in which agents learn new skills by interacting with other agents. It is well known that many natural species have evolved a capacity to use information provided by other individuals to enhance their individual skills. However, only in the last decade researches in artificial life, adaptive behavior, evolutionary robotics and, more generally, embodied dynamical systems started to focus explicitly on the features and outcomes of social learning dynamics. The artificial modeling of social learning allows researchers to shed new lights on a wide range of phenomena that play an important role in the evolution of complex behaviors in natural organisms and a fundamental role in the evolution of complex behaviors in humans. The study of social learning, the mechanisms on which it relies, its outcomes on collective and individual behavioral dynamics and its relationships with other adaptation processes (e.g. individual learning, genetic evolution) represent an exciting subfield of artificial life research.
:: timeline
18. 5. 07 :: full paper submission
8. 6. 07 :: notification of acceptance
18. 6. 07 :: camera ready submission
10 .9. 07 :: workshop in
Lisbon!
When considering behavior as a complex outcome resulting form the interactions between different levels such as body, nervous system, and physical and social environment, an embodied approach to behavior seems particularly promising for the study of social learning phenomena as they typically depend on several hierarchical relationship. Indeed, empirical observations, laboratory experiments and "traditional" analytical modeling often experience difficulties in managing that complexity.
The aim of the workshop will be twofold. Although a consistent number of successful social learning models have been realized in the last years, the field is still fragmented. The workshop will try to point out the shared results and the common open issues in order to contribute to the definition of the specificity of the embodied approach to social learning, as well as its connections with other approaches, inside and outside Artificial Life. Moreover, it will be an opportunity to review the recent advances on a fast developing field that can be relevant for many attendants of the ECAL conference.
See also the parallel workshop on the emergence of social behaviour.
:: invited speakers
Malinda Carpenter - Max Planck Institute for Evolutionary Anthropology, Leipzig, Deutschland
"Shared Intentionality in Imitation" [abstract .pdf]
Bennett G. Galef, Jr. - McMaster University, Hamilton, Canada
"Testing predicitons from formal models of social learning: When should animals increase use of socially acquired information?" [abstract .pdf]
:: organizing committee
Alberto Acerbi - Institute of Cognitive Sciences
and Technology, CNR, Rome, Italy
Davide Marocco - Institute of Cognitive Sciences and Technology, CNR,
Rome, Italy
Paul Vogt - Language and Information Science, Tilburg University, Tilburg,
The Netherlands
:: scientific committee
Tony Belpaeme - University of Plymouth
Aude Billard - Ecole Polytechnique Fédérale de Lausanne
Angelo Cangelosi - University of Plymouth
Kerstin Dautenhahn - University of Hertfordshire
Yiannis Demiris - Imperial College London
Takashi Ikegami - University of Tokio
Chrystopher Nehaniv - University of Hertfordshire
Stefano Nolfi - Institute of Cognitive Science and Technology, Rome
Domenico Parisi - Institute of Cognitive Science and Technology, Rome
Andrew Smith - University of Edinburgh
Elio Tuci - Université Libre de Bruxelles
:: funding
The Workshop is funded by Eucognition - European Network for the Advancement of Artificial Cognitive Systems
