A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation

TL;DR

This paper introduces SALDAE, a multiagent path finding algorithm designed for large-scale coalition structure generation, enabling rapid high-quality solutions in complex multiagent systems.

Contribution

The paper presents SALDAE, a novel heuristic-based multiagent path search algorithm that efficiently handles large coalition structure generation problems.

Findings

SALDAE finds high-quality solutions rapidly.

It outperforms existing methods on standard benchmarks.

It scales to problems with hundreds and thousands of agents.

Abstract

Coalition structure generation (CSG), i.e. the problem of optimally partitioning a set of agents into coalitions to maximize social welfare, is a fundamental computational problem in multiagent systems. This problem is important for many applications where small run times are necessary, including transportation and disaster response. In this paper, we develop SALDAE, a multiagent path finding algorithm for CSG that operates on a graph of coalition structures. Our algorithm utilizes a variety of heuristics and strategies to perform the search and guide it. It is an anytime algorithm that can handle large problems with hundreds and thousands of agents. We show empirically on nine standard value distributions, including disaster response and electric vehicle allocation benchmarks, that our algorithm enables a rapid finding of high-quality solutions and compares favorably with other state-of-the-art methods.