Socially Intelligent Agents

1. Front Matter

   Pages i-xv

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2. Socially Intelligent Agents

   • Kerstin Dautenhahn, Alan Bond, Lola Cañamero, Bruce Edmonds

   Pages 1-20

3. Understanding Social Intelligence

   • Per Persson, Jarmo Laaksolahti, Peter Löonnqvist

   Pages 21-28

4. Modeling Social Relationship

   • Alan H. Bond

   Pages 29-36

5. Developing Agents Who Can Realte to Us

   • Bruce Edmonds

   Pages 37-44

6. Party Hosts and Tour Guides

   • Katherine Isbister

   Pages 45-52

7. Increaing Sia Architecture Realism by Modeling and Adapting to Affect and Personality

   • Eva Hudlicka

   Pages 53-60

8. Cooperative Interface Agents

   • Sebastiano Pizzutilo, Berardina De Carolis, Fiorella de Rosis

   Pages 61-68

9. Playing the Emotion Game with Feelix

   • Lola D. Cañamero

   Pages 69-76

10. Creating Emotion Recognition Agents for Speech Signal

    • Valery A. Petrushin

    Pages 77-84

11. Social Intelligence for Computers

    • Juliette Rouchier

    Pages 85-92

12. Egochat Agent

    • Hidekazu Kubota, Toyoaki Nishida

    Pages 93-100

13. Electric Elves

    • David V. Pynadath, Milind Tambe

    Pages 101-108

14. Building Empirically Plausible Multi-Agent Systems

    • Edmund Chattoe

    Pages 109-116

15. Robotic Playmates

    • Kerstin Dautenhahn, Iain Werry, John Rae, Paul Dickerson, Penny Stribling, Bernard Ogden

    Pages 117-124

16. Mobile Robotic Toys and Autism

    • François Michaud, Catherine Théberge-Turmel

    Pages 125-132

17. Affective Social Quest

    • Katharine Blocher, Rosalind W. Picard

    Pages 133-140

18. Pedagogical Soap

    • Stacy C. Marsella

    Pages 141-148

19. Designing Sociable Machines

    • Cynthia Breazeal

    Pages 149-156

20. Infanoid

    • Hideki Kozima

    Pages 157-164

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.

• Artificial intelligence
• Multi-agent system
• Racter
• affective computing
• anthropomorph
• autonom
• autonomous agent
• cognition
• emotion
• emotion recognition
• human-computer interaction (HCI)
• mobile robot
• modeling
• robotics
• therapy

• University of Hertfordshire, UK

  Kerstin Dautenhahn, Lola Cañamero

• California Institute of Technology, USA

  Alan Bond

• Manchester Metropolitan University, Manchester, UK

  Bruce Edmonds

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