Faster Optimal Coalition Structure Generation via Offline Coalition Selection and Graph-Based Search

TL;DR

The paper introduces SMART, a novel hybrid algorithm that significantly improves the speed of generating optimal coalition structures in multi-agent systems by combining dynamic programming, offline coalition selection, and graph-based search techniques.

Contribution

It presents a new hybrid algorithm, SMART, that enhances coalition structure generation efficiency through innovative offline and graph-based methods, outperforming prior algorithms.

Findings

SMART is faster than prior algorithms like ODP-IP and BOSS.

The hybrid approach improves the precision and efficiency of coalition structure generation.

Experimental results show consistent performance across various value distributions.

Abstract

Coalition formation is a key capability in multi-agent systems. An important problem in coalition formation is coalition structure generation: partitioning agents into coalitions to optimize the social welfare. This is a challenging problem that has been the subject of active research for the past three decades. In this paper, we present a novel algorithm, SMART, for the problem based on a hybridization of three innovative techniques. Two of these techniques are based on dynamic programming, where we show a powerful connection between the coalitions selected for evaluation and the performance of the algorithms. These algorithms use offline phases to optimize the choice of coalitions to evaluate. The third one uses branch-and-bound and integer partition graph search to explore the solution space. Our techniques bring a new way of approaching the problem and a new level of precision to the field. In experiments over several common value distributions, we show that the hybridization of these techniques in SMART is faster than the fastest prior algorithms (ODP-IP, BOSS) in generating optimal solutions across all the value distributions.