An Evolutionary Spatial Game-based Approach for the Self-regulation of Social Exchanges in MAS

Abstract

An open problem in social simulation and MAS applications is the self-regulation of social exchange processes, aiming at the achievement/maintenance of equilibrated exchanges by the agents themselves, providing the continuation of the interactions in time. This paper faces this problem through an approach based on the proposed spatial and evolutionary Game of Self-Regulation of Social Exchange Processes. The agents, adopting different social exchange strategies, which take into account both the short and long-term aspects of interactions, evolve such strategies by themselves in time, in order to maximize their respective strategy-based fitness functions. In consequence, the agents happen to perform more equilibrated and fair interactions, increasing the number of successful exchanges.