Robust Coalition Structure Generation

Tenda Okimoto, Nicolas Schwind, Emir Demirovic, Katsumi Inoue, Pierre Marquis

Abstract: How to form effective coalitions is an important issue in multi-agent systems. Coalition Structure Generation ( $$\mathsf {CSG}$$ ) involves partitioning a set of agents into coalitions so that the social surplus (i.e. the sum of the rewards obtained by each coalition) is maximized. In many cases, one is interested in computing a partition of the set of agents which maximizes the social surplus, but is robust as well, which means that it is not required to recompute new coalitions if some agents break down. In this paper, the focus is laid on the Robust Coalition Structure Generation ( $$\mathsf {RCSG}$$ ) problem. A formal framework is defined and some decision and optimization problems for $$\mathsf {RCSG}$$ are pointed out. The computational complexity of $$\mathsf {RCSG}$$ is then identified. An algorithm for $$\mathsf {RCSG}$$ (called $$\mathsf {AmorCSG}$$ ) is presented and evaluated on a number of benchmarks.