Coalition Structure Generation based on Distributed Constraint Optimization

Forming effective coalitions is a major research challenge in AI and multi-agent systems (MAS). Coalition Structure Generation (CSG) involves partitioning a set of agents into coalitions so that social surplus (the sum of the rewards of all coalitions) is maximized. A partition is called a coalition structure (CS). In traditional works, the value of a coalition is given by a black box function called a characteristic function. In this paper, we propose a novel formalization of CSG, i.e., we assume that the value of a characteristic function is given by an optimal solution of a distributed constraint optimization problem (DCOP) among the agents of a coalition. A DCOP is a popular approach for modeling cooperative agents, since it is quite general and can formalize various application problems in MAS. At first glance, one might imagine that the computational costs required in this approach would be too expensive, since we need to solve an NP-hard problem just to obtain the value of a si...

• Type: Conference
• Year: 2010
• Where: AAAI
• Authors: Suguru Ueda, Atsushi Iwasaki, Makoto Yokoo, Marius-Calin Silaghi, Katsutoshi Hirayama, Toshihiro Matsui
• Keywords: AAAI 2010, Coalition, Coalition Structure, DCOP, Intelligent Agents