Feasible Formation of Coalitions Among Autonomous Agents in Nonsuperadditive Environments

Abstract

Cooperating and sharing resources by creating coalitions of agents are an important way for autonomous agents to execute tasks and to maximize payoff. Such coalitions will form only if each member of a coalition gains more if it joins the coalition than it could gain otherwise. There are several ways of creating such coalitions and dividing the joint payoff among the members. In this paper we present algorithms for coalition formation and payoff distribution in non-super-additive environments. We focus on a low-complexity kernel-oriented coalition formation algorithm. The properties of this algorithm were examined via simulations. These have shown that the model increases the benefits of the agents within a reasonable time period, and more coalition formations provide more benefits to the agents.