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Thu, 23 Oct 1997 14:56:04 +0100
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                     CALL FOR PAPERS


                    Full-day Workshop
                       May 9, 1998
                   Minneapolis/St. Paul

                      Associated with
Second International Conference on  AUTONOMOUS AGENTS (Agents '98)
            Minneapolis/St. Paul, May 10-13, 1998

Co-organisers:  Kerstin Dautenhahn* and Gillian Hayes**

*Department of Cybernetics, University of Reading, UK
**Department of Artificial Intelligence, University of Edinburgh, UK

The scope of the workshop encompasses social learning and imitation as
a means of one agent, software or embodied, learning an individual
behaviour pattern or utterance from a member of the same or a
different species and including it in its own behavioural repertoire.
The workshop is intended to attract people from different communities
where social learning and imitation is involved, i.e. where agents
learn from each other or their users through interaction.

- machine learning
- robotics
- human-computer interaction
- adaptive user interfaces
- programming by demonstration
- social learning in virtual environments
- case-based reasoning
- multi-media environments supporting social learning
- interactive art
- biological/ethological models of social learning
- psychology of social learning
... related topics

Imitation is supposed to be among the least common and most complex
forms of animal learning. It is found in highly socially living
species which show, from a human observer point of view, 'intelligent'
behaviour and signs for the evolution of traditions and culture. There
is strong evidence for imitation in certain primates (humans and
chimpanzees), cetaceans (whales and dolphins) and specific birds like
parrots. Recently, imitation has begun to be studied in domains
dealing with such non-natural agents as robots, as a tool for easing
the programming of complex tasks or endowing groups of robots 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
their 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 the agent's own behavioural

The role of imitation as an effective learning mechanism is important
in engineering domains. The main aims are to develop imitation as a
machine learning method for an agent, allowing it to learn from one or
very few examples which are performed by a model, and to facilitate
indirect knowledge transfer from one agent to another. The latter
becomes more and more interesting for scenarios where interactions
between heterogeneous agents are studied, because in these situations
the simple transfer of a successful control program from one agent to
another is often impossible because of great differences in
construction and behavior characteristics.  Examples include the use
of imitation of movements by a robot to learn a navigation task, and
the acquisition of a synthetic robotic language by observation.  The
obvious extension is to situations where the agent has to learn from a
human `model' in, for example, the context of service robots which
must adapt to humans and cooperate/work hand-in-hand together with
humans.  In Artificial Life research on individualized robot
societies, imitation is used as a social mechanism for identifying and
building up social relationships towards robot group members. In
Software Agent research, imitation is used as a means of enabling
agents to adapt to one another and develop a coherent group behaviour.

As a research topic imitation tackles such fundamental problems as
sensory intelligence, motor control, real-time learning architectures,
intermodal representation, social interactions, motivational and
emotional control of behavior, and scaling-up from sensorimotor
intelligence to cognitive systems. Generally, different mechanisms are
studied in these different domains, so the problem arises of
integrating them in a common framework.  The topic of imitation is
broad enough to cover all these interesting issues.

The aim of the workshop is to draw together researchers working in
software, hardware and wetware fields with the common goal of
understanding the role of social learning in making agents useful,
believable, acceptable or simply natural.

The Workshop will comprise a few keynote talks, a panel discussion
with participants from different research areas, and sessions with
presentation of state-of-the-art social learning and imitation

People who are interested in participating in the workshop are asked
to submit an extended abstract (not more than 4 pages).  Please submit
4 hardcopies to:

Kerstin Dautenhahn
Department of Cybernetics
The University of Reading
Whiteknights, PO Box 225
Reading, RG6 6AY, United Kingdom
tel: +44 (0) 118 931-8219       or -6372
fax: +44 (0) 118 931-8220
[log in to unmask]

An email submission in plain ascii format is also possible, postscript
submissions cannot be accepted.

January 15, 1998: Workshop papers due
February 28, 1998:  Notification
March 30, 1998: Final Copies for Workshop Notes Due

Kerstin Dautenhahn (University of Reading, UK)
Gillian Hayes (University of Edinburgh, UK)
Roy Middleton (Edinburgh Virtual Environment Centre, UK)
Peter McOwan (University of Reading, UK)
Simon Penny (CMU, USA)
Paolo Petta (Austrian Research Institute for Artificial Intelligence)
Angi Voss (GMD, Germany)