Justifying and Improving Meta-Agent Conflict-Based Search
This work addresses a domain-specific issue in multi-agent path finding by providing incremental improvements to an existing algorithm, enhancing its efficiency and adaptability.
The paper tackled the problem of improving the Meta-Agent Conflict-Based Search (MA-CBS) algorithm for multi-agent path finding by addressing its reliance on an empirically chosen fixed threshold for merging agents, which varies with domain and agent count. They proposed new decision policies based on a model analysis, resulting in considerable performance improvements, as evaluated on multiple problem sets.
The Meta-Agent Conflict-Based Search~(MA-CBS) is a recently proposed algorithm for the multi-agent path finding problem. The algorithm is an extension of Conflict-Based Search~(CBS), which automatically merges conflicting agents into meta-agents if the number of conflicts exceeds a certain threshold. However, the decision to merge agents is made according to an empirically chosen fixed threshold on the number of conflicts. The best threshold depends both on the domain and on the number of agents, and the nature of the dependence is not clearly understood. We suggest a justification for the use of a fixed threshold on the number of conflicts based on the analysis of a model problem. Following the suggested justification, we introduce new decision policies for the MA-CBS algorithm, which considerably improve the algorithm's performance. The improved variants of the algorithm are evaluated on several sets of problems, chosen to underline different aspects of the algorithms.