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CONNECTION SCIENCE JOURNAL

Special Issue on SOCIAL LEARNING IN EMBODIED AGENTS

Guest Editors: Alberto Acerbi, Davide Marocco, Paul Vogt

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 research
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.

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 relationships.

Although a consistent number of successful social learning models have been
realized in the past years, the field is still fragmented. The aim of the
special issue is 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.

Original papers - both tecnical and conceptual - on any aspect of embodied
social learning are welcome. Topics include, but are not restricted to:

* Social learning and the evolution of communication
* Imitation in embodied agents
* Cultural evolutionary dynamics
* Interactions between genetic evolution, individual and social learning
* Relationship between individual behavior and populational dynamics
* Models of simple mechanisms of social learning
* Action, perception, and cognition in social interactions
* Cultural factors that affect social and individual behavior
* Niche construction in social environment
* Collective behavior in learning robot
* Teaching and scaffolding of behavior
* Dynamic role allocation
* Self organization in social learning

SUBMISSION INSTRUCTIONS

All manuscripts should be emailed to the guest editor (Alberto Acerbi,
alberto.acerbi[at]istc.cnr.it). Instructions for authors are available from:
http://www.tandf.co.uk/journals/authors/ccosauth.asp.


IMPORTANT DATES

full paper submission :: 30 October 2007

review deadline :: 15 December 2007

notification of acceptance :: 21 December 2007

camera ready submission :: 28 February 2008


GUEST EDITORS

Alberto Acerbi
Institute of Cognitive Science and Technology, Rome, Italy
web: http://laral.istc.cnr.it/acerbi/

Davide Marocco
Institute of Cognitive Science and Technology, Rome, Italy
web: http://laral.istc.cnr.it/marocco/

Paul Vogt
Communication and Information Science, Tilburg University, Tilburg, The
Netherlands
web: http://www.ling.ed.ac.uk/~paulv/


ABOUT THE JOURNAL

Connection Science is an interdisciplinary scientific journal with a focus
on the mechanisms of adaptation, cognition and intelligent behaviour in both
living and artificial systems. The traditional scope of the journal has been
broadened from connectionist research and neural computing to encompass work
on other adaptive methods (e.g. evolutionary computing) as well as
biologically inspired techniques and algorithms in applied domains.

Papers submitted to the journal may be practical implementations,
theoretical research or philosophical discussions. The submission of
robotics research papers on issues raised by the interaction of agents with
the environment or with other agents is particularly encouraged.