Coalition Structure Generation Utilizing Compact Characteristic Function Representations

This paper presents a new way of formalizing the Coalition Structure Generation problem (CSG), so that we can apply constraint optimization techniques to it. Forming effective coalitions is a major research challenge in AI and multi-agent systems. CSG involves partitioning a set of agents into coalitions so that social surplus is maximized. Traditionally, the input of the CSG problem is a black-box function called a characteristic function, which takes a coalition as an input and returns the value of the coalition. As a result, applying constraint optimization techniques to this problem has been infeasible. However, characteristic functions that appear in practice often can be represented concisely by a set of rules, rather than a single black-box function. Then, we can solve the CSG problem more efficiently by applying constraint optimization techniques to the compact representation directly. We present new formalizations of the CSG problem by utilizing recently developed compact repr...

• Type: Conference
• Year: 2009
• Where: CP
• Authors: Naoki Ohta, Vincent Conitzer, Ryo Ichimura, Yuko Sakurai, Atsushi Iwasaki, Makoto Yokoo
• Keywords: Constraint Optimization Techniques, CP 2009, CSG Problem, Efficient Constraint Optimization, Programming Languages