Design of Social Agents

Social behavior, as compared to the egoistic and rational behavior, is known to be more beneficial to groups of subjects and even to individual members of a group. For this reason, social norms naturally emerge as a product of evolution in human and animal populations. The benefit of the social behavior makes it also an interesting subject in the field of artificial agents. Social interactions implemented in computer agents can improve their personal and group performance. In this study we formulate design principles of social agents and use them to create social computer agents. To construct social agents we take two approaches. First, we construct social computer agents based on our understanding of social norms. Second, we use an evolutionary approach to create social agents. The social agents are shown to outperform agents that do not utilize social behavior.

[1]  J. Pfeffer,et al.  The External Control of Organizations. , 1978 .

[2]  Dieter Vanderelst,et al.  Simulated trust: a cheap social learning strategy. , 2009, Theoretical population biology.

[3]  Matthias Rauterberg,et al.  State-coupled replicator dynamics , 2009, AAMAS.

[4]  Matthias Rauterberg,et al.  Entertainment Computing in the Orbit , 2008, ECS.

[5]  Andrew Whiten,et al.  Spread of arbitrary conventions among chimpanzees: a controlled experiment , 2007, Proceedings of the Royal Society B: Biological Sciences.

[6]  Andrew Whiten,et al.  Transmission of Multiple Traditions within and between Chimpanzee Groups , 2007, Current Biology.

[7]  Matthias Rauterberg,et al.  Nonverbal Behavior Observation: Collaborative Gaming Method for Prediction of Conflicts during Long-Term Missions , 2010, ICEC.

[8]  Mark A. Neerincx,et al.  MICRO-SCALE SOCIAL NETWORK ANALYSIS FOR ULTRA-LONG SPACE FLIGHTS , 2009, IJCAI 2009.

[9]  R. Grant The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation , 1991 .

[10]  M. Tomasello The Cultural Origins of Human Cognition , 2000 .

[11]  Emilia I. Barakova,et al.  Simulated Trust - Towards robust social learning , 2008, ALIFE.

[12]  Pietro Liò,et al.  Bio-Inspired Multi-agent Collaboration for Urban Monitoring Applications , 2008, BIOWIRE.

[13]  W. Powell,et al.  The iron cage revisited institutional isomorphism and collective rationality in organizational fields , 1983 .

[14]  Emilia I. Barakova,et al.  Design for social interaction through physical play in diverse contexts of use , 2009, Personal and Ubiquitous Computing.

[15]  Avi Pfeffer,et al.  Modeling how humans reason about others with partial information , 2008, AAMAS.

[16]  E. Barakova,et al.  Social training of autistic children with interactive intelligent agents. , 2009, Journal of integrative neuroscience.

[17]  Emilia I. Barakova,et al.  Expressing and interpreting emotional movements in social games with robots , 2010, Personal and Ubiquitous Computing.