Please circulate to colleagues who might be interested to submit. Thank you.
Kerstin Dautenhahn and Chrystopher Nehaniv
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Call For Papers
IMITATION IN NATURAL & ARTIFICIAL SYSTEMS
Special Issue of the International Journal
CYBERNETICS AND SYSTEMS
published by
Taylor & Francis
edited by
Chrystopher L. Nehaniv and Kerstin Dautenhahn
*** Submissions due: 1 October 1999 ***
High quality journal submissions reporting original scientific work are
invited for a special issue of the journal Cybernetics and Systems on the
topic of Imitation in Natural and Artificial Systems.
Imitation is one of the most important mechanisms whereby knowledge can be
transferred between agents (biological, computational or robotic autonomous
systems). Both natural and artificial systems are of interest for this
interdisciplinary area. The importance of imitation has grown increasingly
in cognitive and social sciences, developmental psychology, animal
behavior, artificial intelligence, robotics, programming by example
(instructible agents), machine learning, user-interface design, cybernetics
and systems, and other areas.
The areas of interest of the special issue include but are not limited to:
* Trying to Imitate - solving the correspondence problem between
differently embodied systems
* Learning by Imitation - harnessing imitation as a means to bootstrap
acquisition of knowledge and appropriate behaviors
* Learning of Perception-Action Mappings via Observation of the Self or
Others (an instance of the correspondence problem)
* Imitation in Animals (studies and models, theories, comparisons to
mechanisms of Social Learning)
* Imitation in Developmental Psychology, Language Games
* Imitation in Play and Creativity
* Memetics and Cultural Transmission
* Origin, Evolution and Maintenance of Signs and Semiotic Systems
* Social Intelligence (role of cognitive capacities, emotions, internal
states, and behavioral competencies, understanding of self and others)
* Mimicry & Deception
* Robot Imitation (experiments, architectures, role of memory and
prediction, learning sequences of actions and acquiring behaviors)
* Algebra and Dynamics of Imitation
* Useful Formalization of Imitation: 1) metrics on imitative behaviors
as observed externally, 2) specification of the agent's
internal/cognitive processes resulting in the observed behavior;
* Applications in Interactive Systems (CAI, User-Interface Design,
Cognitive Technology, customization, mimetic agent technology, social
intelligence, semiotic & linguistic systems, automated software
generation)
* Neuroscience & Machine Approaches to Motion Perception and Imitative
Actions
* Imitation & Intent (relations to Cognitive Robotics, theory of other
minds, empathy, 1st / 2nd person methods, affective computing,
deliberation vs. reactivity, situated planning & teamwork)
Imitation is believed to be among the least common and most complex forms
of animal learning. It is found in highly social species which show, from a
human observer point of view, 'intelligent' behavior and traits supporting
the evolution of traditions and culture. Recently, imitation has begun to
be studied in domains dealing with such non-natural agents as robots, and
as a tool for easing the programming of complex tasks or endowing groups of
robotic agents with the ability to share skills without the intervention of
a programmer. Imitation plays an important role in the more general context
of interaction and collaboration between agents and humans, e.g. between
software agents and human users. Intelligent software agents need to get to
know their users in order to assist them and do productive work on behalf
of humans. Imitation is therefore a means of establishing a 'social
relationship' and learning about the actions of the user, in order include
them into an agent's own behavioral repertoire.
Imitation is on the one hand considered as an efficient mechanism of social
learning. On the other hand, imitation methods as in programming by
demonstration setups in robotics and machine learning have primarily
focused on the technological dimensions, while disregarding the more social
and developmental functions. Additionally, the split between imitation
research in natural sciences and the sciences of the artificial has been
difficult to bridge, as we lack a common framework supporting an
interdisciplinary approach. Yet, studying imitation for an embodied system
inhabiting a non-trivial environment leads one to address all major AI
problems from a new perspective: perception-action coupling, body-schemata,
learning of sequences of action, recognition and matching of movements,
contextualization, reactive and cognitive aspects of behavior, the
development of sociality, or the notion of `self', just to mention a few
issues.
Imitation involves at least two agents sharing a context, allowing one
agent to learn from the other. The exchange of skills, knowledge, and
experience between natural agents cannot be achieved by brain-to-brain
communication but is mediated via bodies, the environment, the verbal or
non-verbal expression or body language of the `sender', which in return has
to be interpreted and integrated in the `recipient's' own understanding and
behavioral repertoire. Moreover, as imitation games between babies and
parents show, the metaphor of `sender' and `receiver' is deceptive, since
the game emerges from the engagement of both agents in the interaction (cf.
notions of situated activity and interactive emergence). Thus, learning by
imitation and learning to imitate are not just a specific topics in machine
learning, but can be seen as a benchmark challenges for successful
real-world AI Systems.
Following on the success of the recent symposium of the Society for the
Study of Artificial Intelligence and Simulation of Behaviour (AISB) on
Imitation in Animals and Artifacts, also organized by the editors of the
special issue, the journal publication is expected to include, among other
submissions, journal length extensions of some excellent papers presented
at the symposium reporting original work meriting attention of the growing
indisciplinary international community concerned with studies of imitation
in natural and artificial systems. All submissions will be peer-reviewed.
Authors should adhere to the instructions for authors available on the Web
at http://www.taylorandfrancis.com/authors/cbsauth.htm when submitting your
first drafts for review. Suggested length of submissions is around 20-30
pages, adhering to the formatting instructions.
Authors are requested to inform the editors of the topic of a planned
submission as soon as possible in advance of submission and to submit
papers well before the deadline if possible in order to expedite the review
process.
------------------------------------------------------------------------
Important Dates:
* Submission of papers: 1 October 1999
* Reviews due to authors: 15 December 1999
* Camera ready papers due: 15 February 2000
------------------------------------------------------------------------
How to submit:
Electronic submission is strongly encouraged:
Send a PostScript version of your article by electronic mail to
[log in to unmask] as an attachment, or compressed and uuencoded.
However, you may alternatively send three (3) hardcopies of your paper to:
Dr. C. L. Nehaniv (Cybernetics & Systems)
Interactive Systems Engineering
University of Hertfordshire
College Lane
Hatfield Herts AL10 9AB
United Kingdom
Any questions concerning the appropriateness of planned submissions or
other queries may be directed to the editors:
Chrystopher Nehaniv Kerstin Dautenhahn
University of Hertfordshire University of Reading
[log in to unmask] [log in to unmask]
http://www.cyber.rdg.ac.uk/people/kd/WWW/CBSimitation.html
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