Justifying and Improving Meta-Agent Conflict-Based Search

TL;DR

This paper analyzes and justifies the use of fixed conflict thresholds in Meta-Agent Conflict-Based Search for multi-agent pathfinding, proposing new policies that significantly enhance its performance across various problem sets.

Contribution

It provides a theoretical justification for fixed conflict thresholds in MA-CBS and introduces improved decision policies that outperform previous versions.

Findings

New decision policies significantly improve MA-CBS performance

The justification based on model problem analysis supports fixed threshold use

Evaluations show consistent performance gains across multiple problem sets

Abstract

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.