[alife] EXTENDED DEADLINE: Connection Science: Special issue on Social Learning in Embodied Agents

[Davide Marocco]

Please, accept our apologies for multiple postings.

------------------------------------------------------------------------
--------

FULL PAPER SUBMISSION EXTENDED DEADLINE:
19 November 2007

------------------------------------------------------------------------
--------


---------------------------------------------------
CALL FOR PAPERS
---------------------------------------------------

CONNECTION SCIENCE JOURNAL

Special Issue on SOCIAL LEARNING IN EMBODIED AGENTS

Following the ECAL2007 Workshop on " Social Learning In Embodied Agents"
URL: http://laral.istc.cnr.it/slea/index.html

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 from 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 technical 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 population 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 :: 19 November 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
School of Computing, Communications & Electronics, University of
Plymouth, Plymouth, UK
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.