A generalized particle model for social coordination and autonomy in MAS

Abstract

In multi-agent systems (MAS), every autonomous agent tries to increase its own personal utility under complex environment involving a variety of types of social coordination. Modeling the social coordination and autonomy of agents is of great significance for distributed problem-solving in MAS. This paper is devoted to a novel generalized particle approach to model social coordination and autonomy in MAS. At first, we analyze and formalize some typical types of social coordination in MAS. Then we discuss the generalized particle model (GPM) for distributed problem-solving in MAS that is related to social coordination and social dynamics. Finally, we demonstrate the GPM-based parallel algorithm and its properties for parallel distributed task allocation and resource assignment in MAS.