Social identity theory applied to the game of self-regulation of social exchanges based on multiagent systems

Autonomous intelligent agents participate in complex social situations. It is necessary that agents are aware of their society and still understand their context of action and interaction. Such social situation with other agents is influenced by society’s characteristics, including their norms, values, common interests and objectives, members, and social structures. Each complex society is broken down into social groups, each one with an identity. Social identity theory is seen as an analysis of intergroup relations in social categories based on the cognitive definition and the autoconcept of a social group and their belonging. Researchers have been studying this theory in computing, more specifically in multiagent systems. Social exchanges are the object of study in diverse contexts in which social relations are understood as social exchanges. One of the investigated themes is the self-regulation of social exchanges. The game of self-regulation of social exchanges explores its self-regulation but it does not analyse the agents’ identity. Therefore, this research investigates the integration of psychosocial analysis of social identity theory into the social adaptive complex society of the game of self-regulation of social exchanges. The principal result of this work is the GSRSEPSIT, a social simulation model.