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In coalition formation with self-interested agents both social welfare of the multi-agent system and stability of individual coalitions must be taken into account. However, in large-scale systems with thousands of agents, finding an optimal solution with respect to both metrics is infeasible. In this paper we propose an approach for finding coalition structures with suboptimal social welfare and coalition stability in largescale multi-agent systems. Our approach uses multi-agent simulation to model a dynamic coalition formation process. Agents are allowed to deviate from unstable coalitions, thus increasing the coalition stability. Furthermore we present an approach for estimating coalition stability, which alleviates exponential complexity of coalition stability computation. This approach is used for estimating stability of multiple coalition structures generated by the multi-agent simulation, which enables us to select a solution with high values of both social welfare and coalition stability. We experimentally show that our algorithms cause a major increase in coalition stability compared to a baseline social welfare-maximizing algorithm, while maintaining a very small decrease in social welfare.

Increasing Coalition Stability in Large-Scale Coalition Formation with Self-Interested Agents