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Socially situated planning provides one mechanism for improving the
social awareness ofagents. Obviously this work isin the preliminary
stages and many of the limitation and the relationship to other
work could not be addressed in such a short chapter. The chief
limitation, of course, is the strong commitment to de?ning social
reasoning solely atthe meta-level, which restricts the subtlety of
social behavior. Nonetheless, our experience in some real-world
military simulation applications suggest that the approach, even in
its preliminary state, is adequate to model some social
interactions, and certainly extends the sta- of-the art found in
traditional training simulation systems. Acknowledgments This
research was funded by the Army Research Institute under contract
TAPC-ARI-BR References [1] J. Gratch. Emile: Marshalling passions
in training and education. In Proceedings of the Fourth
International Conference on Autonomous Agents, pages 325-332, New
York, 2000. ACM Press. [2] J. Gratch and R. Hill. Continous
planning and collaboration for command and control in joint
synthetic battlespaces. In Proceedings of the 8th Conference on
Computer Generated Forces and Behavioral Representation, Orlando,
FL, 1999. [3] B. Grosz and S. Kraus. Collaborative plans for
complex group action. Arti?cial Intelli gence, 86(2):269-357, 1996.
[4] A. Ortony, G. L. Clore, and A. Collins. The Cognitive Structure
of Emotions. Cambridge University Press, 1988. [5]
R.W.PewandA.S.Mavor,editors. Modeling Human and Organizational
Behavior. National Academy Press, Washington D.C., 1998.
Socially situated planning provides one mechanism for improving the
social awareness ofagents. Obviously this work isin the preliminary
stages and many of the limitation and the relationship to other
work could not be addressed in such a short chapter. The chief
limitation, of course, is the strong commitment to de?ning social
reasoning solely atthe meta-level, which restricts the subtlety of
social behavior. Nonetheless, our experience in some real-world
military simulation applications suggest that the approach, even in
its preliminary state, is adequate to model some social
interactions, and certainly extends the sta- of-the art found in
traditional training simulation systems. Acknowledgments This
research was funded by the Army Research Institute under contract
TAPC-ARI-BR References [1] J. Gratch. Emile: Marshalling passions
in training and education. In Proceedings of the Fourth
International Conference on Autonomous Agents, pages 325-332, New
York, 2000. ACM Press. [2] J. Gratch and R. Hill. Continous
planning and collaboration for command and control in joint
synthetic battlespaces. In Proceedings of the 8th Conference on
Computer Generated Forces and Behavioral Representation, Orlando,
FL, 1999. [3] B. Grosz and S. Kraus. Collaborative plans for
complex group action. Arti?cial Intelli gence, 86(2):269-357, 1996.
[4] A. Ortony, G. L. Clore, and A. Collins. The Cognitive Structure
of Emotions. Cambridge University Press, 1988. [5]
R.W.PewandA.S.Mavor,editors. Modeling Human and Organizational
Behavior. National Academy Press, Washington D.C., 1998.
This book constiutes the reviewed proceedings of the 4th International Conference on Cognitive Technology, CT 2001, helds in Warwick, UK in August 2001. The 36 revised full papers presented together with six invited papers were carefully reviewed and selected for inclusion in the book. The book offers topical sections on designing artefacts, cognition in robotic and virtual environments, presence in virtual environments, human activity and humnan computing, computing and people education in cognition, learning, narrative and story-telling, interfaces, cognitive dimensions, human work and communities, and human-technology relationship.
Mechanisms of imitation and social matching play a fundamental role
in development, communication, interaction, learning and culture.
Their investigation in different agents (animals, humans and
robots) has significantly influenced our understanding of the
nature and origins of social intelligence. Whilst such issues have
traditionally been studied in areas such as psychology, biology and
ethnology, it has become increasingly recognised that a
'constructive approach' towards imitation and social learning via
the synthesis of artificial agents can provide important insights
into mechanisms and create artefacts that can be instructed and
taught by imitation, demonstration, and social interaction rather
than by explicit programming. This book studies increasingly
sophisticated models and mechanisms of social matching behaviour
and marks an important step towards the development of an
interdisciplinary research field, consolidating and providing a
valuable reference for the increasing number of researchers in the
field of imitation and social learning in robots, humans and
animals.
An interdisciplinary overview of current research on imitation in
animals and artifacts. The effort to explain the imitative
abilities of humans and other animals draws on fields as diverse as
animal behavior, artificial intelligence, computer science,
comparative psychology, neuroscience, primatology, and linguistics.
This volume represents a first step toward integrating research
from those studying imitation in humans and other animals, and
those studying imitation through the construction of computer
software and robots. Imitation is of particular importance in
enabling robotic or software agents to share skills without the
intervention of a programmer and in the more general context of
interaction and collaboration between software agents and humans.
Imitation provides a way for the agent-whether biological or
artificial-to establish a "social relationship" and learn about the
demonstrator's actions, in order to include them in its own
behavioral repertoire. Building robots and software agents that can
imitate other artificial or human agents in an appropriate way
involves complex problems of perception, experience, context, and
action, solved in nature in various ways by animals that imitate.
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