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Since more and more algorithms are proposed for multi-agent path finding (MAPF) and each of them has its strengths, choosing the correct one for a specific scenario that fulfills some specified requirements is an important task. Previous…

Multiagent Systems · Computer Science 2024-04-05 Weizhe Chen , Zhihan Wang , Jiaoyang Li , Sven Koenig , Bistra Dilkina

Anticipating possible future deployment of connected and automated vehicles (CAVs), cooperative autonomous driving at intersections has been studied by many works in control theory and intelligent transportation across decades.…

Multiagent Systems · Computer Science 2024-02-02 Zhongxia Yan , Han Zheng , Cathy Wu

The primary objective of Multi-Agent Pathfinding (MAPF) is to plan efficient and conflict-free paths for all agents. Traditional multi-agent path planning algorithms struggle to achieve efficient distributed path planning for multiple…

Artificial Intelligence · Computer Science 2024-07-18 Zhenyu Song , Ronghao Zheng , Senlin Zhang , Meiqin Liu

Many multi-robot applications require tasks to be completed efficiently and in the correct order, so that downstream operations can proceed at the right time. Multi-agent path finding with precedence constraints (MAPF-PC) is a well-studied…

Robotics · Computer Science 2026-04-01 Viraj Parimi , Brian C. Williams

Multi-Agent Motion Planning (MAMP) is a problem that seeks collision-free dynamically-feasible trajectories for multiple moving agents in a known environment while minimizing their travel time. MAMP is closely related to the well-studied…

Robotics · Computer Science 2024-03-12 Jingtian Yan , Jiaoyang Li

We study the planning and acting phase for the problem of multi-agent path finding (MAPF) in this paper. MAPF is a problem of navigating agents from their start positions to specified individual goal positions so that agents do not collide…

Artificial Intelligence · Computer Science 2022-07-07 Matouš Kulhan , Pavel Surynek

We study the TAPF (combined target-assignment and path-finding) problem for teams of agents in known terrain, which generalizes both the anonymous and non-anonymous multi-agent path-finding problems. Each of the teams is given the same…

Artificial Intelligence · Computer Science 2016-12-20 Hang Ma , Sven Koenig

Multi-Agent Path Finding (MAPF) is the problem of moving multiple agents from starts to goals without collisions. Lifelong MAPF (LMAPF) extends MAPF by continuously assigning new goals to agents. We present our winning approach to the 2023…

Multiagent Systems · Computer Science 2026-03-02 He Jiang , Yulun Zhang , Rishi Veerapaneni , Jiaoyang Li

Multi-Agent Path Finding (MAPF) is the problem of effectively finding efficient collision-free paths for a group of agents in a shared workspace. The MAPF community has largely focused on developing high-performance heuristic search…

Multiagent Systems · Computer Science 2024-09-24 Rishi Veerapaneni , Arthur Jakobsson , Kevin Ren , Samuel Kim , Jiaoyang Li , Maxim Likhachev

Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where agents are constantly engaged with new goal locations, such as…

Artificial Intelligence · Computer Science 2021-03-15 Jiaoyang Li , Andrew Tinka , Scott Kiesel , Joseph W. Durham , T. K. Satish Kumar , Sven Koenig

Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence, where one needs to find collision-free paths for agents with given start and goal locations. In video games, agents of different types often form teams.…

Artificial Intelligence · Computer Science 2017-10-05 Hang Ma , Jingxing Yang , Liron Cohen , T. K. Satish Kumar , Sven Koenig

Multi-Agent Path Finding (MAPF), which focuses on finding collision-free paths for multiple robots, is crucial in autonomous warehouse operations. Lifelong MAPF (L-MAPF), where agents are continuously reassigned new targets upon completing…

Robotics · Computer Science 2025-01-07 Yimin Tang , Zhenghong Yu , Yi Zheng , T. K. Satish Kumar , Jiaoyang Li , Sven Koenig

We propose an extension to the MAPF formulation, called SocialMAPF, to account for private incentives of agents in constrained environments such as doorways, narrow hallways, and corridor intersections. SocialMAPF is able to, for instance,…

Multiagent Systems · Computer Science 2022-10-18 Rohan Chandra , Rahul Maligi , Arya Anantula , Joydeep Biswas

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,…

Artificial Intelligence · Computer Science 2021-09-20 Aysu Bogatarkan

This paper investigates Multi-Agent Path Finding Among Movable Obstacles (M-PAMO), which seeks collision-free paths for multiple agents from their start to goal locations among static and movable obstacles. M-PAMO arises in logistics and…

Robotics · Computer Science 2025-10-01 Shaoli Hu , Shizhe Zhao , Zhongqiang Ren

Among sub-optimal Multi-Agent Path Finding (MAPF) solvers, rule-based algorithms are particularly appealing since they are complete. Even in crowded scenarios, they allow finding a feasible solution that brings each agent to its target,…

Multiagent Systems · Computer Science 2024-10-11 Irene Saccani , Stefano Ardizzoni , Luca Consolini , Marco Locatelli

The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision-free paths for a number of agents, from a set of start locations to a set of goal positions in a known 2D environment. MAPF has been studied in theoretical computer…

Artificial Intelligence · Computer Science 2019-05-22 Gleb Belov , Liron Cohen , Maria Garcia de la Banda , Daniel Harabor , Sven Koenig , Xinrui Wei

Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths for a team of agents. Although several MAPF methods which solve full-horizon MAPF have completeness guarantees, very few MAPF methods that plan partial…

Multiagent Systems · Computer Science 2025-09-22 Tiannan Zhang , Rishi Veerapaneni , Shao-Hung Chan , Jiaoyang Li , Maxim Likhachev

The study addressed the problem of Anonymous Multi-Agent Path-finding (AMAPF). Unlike the classical formulation, where the assignment of agents to goals is fixed, in the anonymous MAPF setting it is irrelevant which agent reaches specific…

Multiagent Systems · Computer Science 2026-03-26 Stepan Dergachev , Dmitry Avdeev

During Multi-Agent Path Finding (MAPF) problems, agents can be delayed by unexpected events. To address such situations recent work describes k-Robust Conflict-BasedSearch (k-CBS): an algorithm that produces coordinated and collision-free…

Artificial Intelligence · Computer Science 2021-10-29 Zhe Chen , Daniel Harabor , Jiaoyang Li , Peter J. Stuckey