Abstract
Social behavior, as compared to the egoistic 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 a social computer agent based on our understanding of social behavior. Second, we use an evolutionary approach to create a social agent. The social agents are shown to outperform agents that do not utilize social behavior.
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