Modeling how humans reason about others with partial information
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Bio-Inspired Multi-agent Collaboration for Urban Monitoring Applications
Bio-Inspired Computing and Communication
State-coupled replicator dynamics
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Design for social interaction through physical play in diverse contexts of use
Personal and Ubiquitous Computing
Expressing and interpreting emotional movements in social games with robots
Personal and Ubiquitous Computing
ICEC'10 Proceedings of the 9th international conference on Entertainment computing
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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.