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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.
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From Animals to Animats 16 - 16th International Conference on Simulation of Adaptive Behavior, SAB 2022, Cergy-Pontoise, France, September 20-23, 2022, Proceedings (Paperback, 1st ed. 2022)
Lola Canamero, Philippe Gaussier, Myra Wilson, Sofiane Boucenna, Nicolas Cuperlier
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R1,560
Discovery Miles 15 600
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 16th
International Conference on Simulation of Adaptive Behavior, SAB
2022, held in Cergy-Pontoise, France, in September 2022. The 17
papers presented in this volume were carefully reviewed and
selected from 23 submissions. They were organized in topical
sections as follows: Embodiment; Brain-Inspired Control,
Adaptation, and Learning; Bio-inspired Vision and navigation;
Affective and Social Cognition and Collective Intelligence.
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