A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation
This addresses the need for efficient coalition structure generation in time-sensitive applications like transportation and disaster response, representing an incremental improvement over existing methods.
The paper tackles the coalition structure generation problem by developing SALDAE, a multiagent path finding algorithm that enables rapid finding of high-quality solutions for large-scale problems with hundreds to thousands of agents, showing favorable comparisons with state-of-the-art methods on nine standard benchmarks.
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.