# Flexible and Explainable Solutions for Multi-Agent Path Finding Problems

arXiv: https://arxiv.org/abs/2109.08299 · HTML: https://mlsanity.com/paper/2109.08299/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 21 references that are in the map.
- First posted on arXiv 17 Sep 2021.

## Builds on (most cited first, 1 of 1)

- [Explanation Generation for Multi-Modal Multi-Agent Path Finding with Optimal Resource Utilization using Answer Set Programming](https://mlsanity.com/paper/2008.03573/) (2020)

## Abstract (arXiv)

The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other, and subject to some constraints on the lengths of paths. The real-world applications of MAPF require flexibility (e.g., solving variations of MAPF) as well as explainability. In this study, both of these challenges are addressed and some flexible and explainable solutions for MAPF and its variants are introduced.