CFP: Symp. on Imitation in Animals and Artifacts

Bruce Edmonds (
Fri, 23 Oct 1998 11:24:42 +0100

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Date: Fri, 23 Oct 1998 11:24:42 +0100
From: Bruce Edmonds <>
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Subject: CFP: Symp. on Imitation in Animals and Artifacts

Symposium on Imitation in Animals
& Artifacts

at the AISB'99 Convention, 6th-9th April
Edinburgh College of Art & Division of
Informatics, University of Edinburgh

Call for Papers

Paper submissions are invited for the Symposium on
Imitation in Animals & Artifacts to be held at the AISB'99
Convention which will be held in Edinburgh in April 1999. It
will consist of 13 workshops and symposia on a wide range of
themes in Artificial Intelligence and Cognitive Science. An
underlying theme of the Convention this year is the study of
creativity, though not all of the events include a creative
element. For further details of AISB'99 will be found at the
conference web site, see

Imitation is one of the most important mechanisms whereby
knowledge is transferred between agents (biological,
computational or robotic autonomous systems). This
symposium will focus on key problems in this important
interdisciplinary area.

The topic of imitation has emerged in various areas close to AI
including cognitive and social sciences, developmental
psychology, animal behavior, robotics, programming by
demonstration, machine learning and user-interface design.

The importance of imitation has grown increasingly apparent to
psychologists, ethologists, philosophers, linguists, cognitive
scientists, computer scientists, mathematicians, biologists,
anthropologists, and roboticists. Yet the workers in the field of
imitation are often unaware of relevant research by others in
other disciplines. The study of imitation has lacked a rigorous
foundation and no major interdisciplinary publication is
available on the subject for workers in AI. The symposium is
aimed toward remedying this situation and will comprise
invited keynote lectures, peer-reviewed contributed
presentations, expert panels and general discussion in the
interdisciplinary area of imitation. This will be achieved by
bringing together established researchers from different areas
and producing a publication which can be used as a standard
reference in research and teaching for the AI community and
others in this exciting field. A rigorously refereed and edited
volume including invited and selected contributed papers will
be published by a major scientific publisher.

The areas of interest of the Symposium on Imitation in
Animals & Artifacts will 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 & appropriate
Imitation in Animals (examples of imitation, theories,
comparisons to mechanisms of social learning)
Imitation in Developmental Psychology, Language
Imitation in Play & Creativity
Memetics & Cultural Transmission
Origin of Signs
Social Intelligence (role of cognitive capacities,
emotions, internal states, & behavioral competencies,
understanding of self & others)
Mimicry & Deception
Robot Imitation (experiments, architectures, role of
memory & prediction, learning sequences of actions)
Algebra & Dynamics of Imitation
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
Imitition & Intent (relations to Cognitive Robotics,
theory of other minds, empathy, 1st / 2nd person
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. 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, 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, and experiments in
developmental psychology suggest that infants use imitation to
get to know others as persons, perhaps by applying a `like-me'
test: `persons are objects which I can imitate and which imitate
me'. 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 in the
same way computers can communicate via the Internet. It 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

The symposium homepage is at

Papers will be selected by anonymous peer review of extended
abstracts of not more than 4 A4 pages. A cover page should be
supplied listing the Title, and the Author's name and
affiliation, but the extended abstract itself should not identify
the author. Deadlines are listed in the timetable, below.

Programme Chairs:

Kerstin Dautenhahn
Department of Cybernetics
University of Reading
Whiteknights, PO Box 225
Reading RG6 6AY
United Kingdom

fax: +44-118-931-6220 tel: +44-118-931-6372

Chrystopher Nehaniv
Interactive Systems Engineering
Faculty of Engineering & Information Sciences
University of Hertfordshire
Hatfield Herts AL10 9AB
United Kingdom

fax: +44-1707-284-303 tel: +44-1707-284-470

Programme Committee:

Aude Billard, Edinburgh, UK;
Cynthia Breazeal, MIT, USA;
Josep Call, Liverpool, UK;
Dolores Caamero, IIIA-CSIC, Spain;
Cristiano Castelfranchi, IP-CNR, Italy;
James P. Crutchfield, UC Berkeley & Santa Fe Institute,
John Demiris, Edinburgh, UK;
Kerstin Dautenhahn, Reading, UK;
Joseph Goguen, UCSD, USA;
David Good, Cambridge Univ., UK;
Horst-Michael Gross, Ilmenau, Germany;
Gillian Hayes, Edinburgh, UK;
Mikael Heimann, Gothenburg, Sweden;
Cecilia Heyes, UCL, UK;
Takashi Ikegami, Tokyo, Japan;
Henry Lieberman, MIT, USA;
Martin Loomes, Hertfordshire, UK;
Yasuo Kuniyoshi, ETL, Japan;
Maja Mataric, USC, USA;
Donald Michie, Edinburgh, UK;
Chrystopher Nehaniv, Hertfordshire, UK;
Paolo Petta, FAI, Austria;
John Rhodes, UC Berkeley, USA;
Brian Scassellati, MIT, USA;
Nestor Schmajuk, Duke, USA;
Maarten Van Someren, Amsterdam, Netherlands,
Stefan Vogt, Lancaster, UK.

Submissions should be sent to the Programme Chairs at the
following address:
Dr. K. Dautenhahn, Department of Cybernetics, University of
Reading, Whiteknights, PO Box 225, Reading RG6 6AY,
United Kingdom.

The following formats are acceptable:
Four hardcopies (any A4 or US Letter format, max. 4 pp.)
via post
Plain ASCII text only electronic submission to

Important Dates:

Submission of Extended Abstracts : 21 December '98
Submission of camera-ready copy : 12 March '99
Notification re: Extended Abstracts : 20 January '99
AISB'99 Convention : 6-9 April '99

The AISB'99 Convention is supported by Edinburgh College
of Art and the Division of Informatics, University of

Local organisers:
Dr Geraint Wiggins & Dr Helen Pain, School of Artificial
Intelligence, Division of Informatics, University of Edinburgh,
80 South Bridge, Edinburgh EH1 1HN, Scotland
{geraint,helen}; Tel:
+44-131-650 2702; Fax: +44-131-650 651

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