# Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks

## TL;DR

This paper reviews the fundamental concepts, variants, and benchmarks of multi-agent pathfinding (MAPF), providing a unified terminology and introducing a new challenging grid-based benchmark for evaluating MAPF algorithms.

## Contribution

It unifies MAPF assumptions and objectives with standardized terminology and introduces a new benchmark to facilitate research and comparison.

## Key findings

- The new grid-based benchmark is challenging for current MAPF algorithms.
- Provides a comprehensive overview of MAPF definitions and variants.
- Offers pointers to existing MAPF benchmarks.

## Abstract

The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Applications of MAPF include automated warehouses and autonomous vehicles. Research on MAPF has been flourishing in the past couple of years. Different MAPF research papers make different assumptions, e.g., whether agents can traverse the same road at the same time, and have different objective functions, e.g., minimize makespan or sum of agents' actions costs. These assumptions and objectives are sometimes implicitly assumed or described informally. This makes it difficult to establish appropriate baselines for comparison in research papers, as well as making it difficult for practitioners to find the papers relevant to their concrete application. This paper aims to fill this gap and support researchers and practitioners by providing a unifying terminology for describing common MAPF assumptions and objectives. In addition, we also provide pointers to two MAPF benchmarks. In particular, we introduce a new grid-based benchmark for MAPF, and demonstrate experimentally that it poses a challenge to contemporary MAPF algorithms.