Jonathan Morag, Noy Gabay, Daniel Koyfman, Roni Stern

Should Multi-Agent Path Finding Algorithms Coordinate Target Arrival Times?

Introduction

Should multi-agent path finding algorithms coordinate target arrival times?. Boost Multi-Agent Path Finding (MAPF) throughput for lifelong tasks. This paper proposes MAPF4L, eliminating restrictive simultaneous target arrival coordination.

Abstract

Multi-Agent Path Finding (MAPF) deals with finding conflict-free paths for a set of agents from an initial configuration to a given target configuration. The Lifelong MAPF (LMAPF) problem is a well-studied online version of MAPF in which an agent receives a new target when it reaches its current target. The common approach for solving LMAPF is to treat it as a sequence of MAPF problems, periodically replanning from the agents’ current configurations to their current targets. A significant drawback of this approach is that in MAPF the agents must reach a configuration in which all agents are at their targets simultaneously. Coordinating the agents’ paths such that they occupy their targets at the same time is needlessly restrictive for LMAPF. Techniques have been proposed to indirectly mitigate this drawback. In this position paper, we describe cases where these mitigation techniques fail. As an alternative, we propose to solve LMAPF problems by solving a sequence of modified MAPF problems, in which the objective is for each agent to eventually visit its target, but not necessarily for all agents to do so simultaneously. We refer to this MAPF variant as MAPF for Lifelong (MAPF4L) and propose how to solve it by modifying several existing MAPF algorithms. A limited experimental evaluation identifies some cases where using a MAPF4L algorithm can improve the system throughput significantly.

Review

This position paper critically examines a fundamental inefficiency in current approaches to Lifelong Multi-Agent Path Finding (LMAPF), specifically the reliance on Multi-Agent Path Finding (MAPF) algorithms that mandate simultaneous agent arrival at target configurations. The authors astutely identify that while LMAPF problems are often solved by sequencing MAPF instances, the simultaneous arrival constraint inherent in traditional MAPF is needlessly restrictive and detrimental to system throughput in a lifelong setting. The paper highlights specific scenarios where existing mitigation techniques, designed to indirectly address this issue, fall short, making a strong case for a more direct conceptual shift. To address this crucial limitation, the paper proposes a novel MAPF variant termed MAPF for Lifelong (MAPF4L). The core innovation of MAPF4L lies in relaxing the simultaneous arrival constraint, requiring only that each agent eventually visits its target rather than all agents converging at their targets concurrently. This redefinition aligns more naturally with the continuous operation of LMAPF systems. The authors suggest that MAPF4L can be solved by modifying several existing MAPF algorithms, thereby offering a practical pathway for implementation without necessitating entirely new algorithmic paradigms. The conceptual clarity and directness of the MAPF4L proposal represent a significant strength, promising a more efficient and intuitive approach to LMAPF. While presented as a position paper with a limited experimental evaluation, the preliminary findings indicating significant throughput improvements strongly suggest that coordinating target arrival times is indeed an unnecessary bottleneck. This paper serves as a valuable call to action for the MAPF community, advocating for a re-evaluation of fundamental assumptions in LMAPF problem solving and laying important groundwork for future research into more robust and performant lifelong multi-agent systems. Further comprehensive empirical validation across diverse scenarios will be crucial to fully quantify and solidify the advantages of the MAPF4L paradigm.

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