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相关论文: Introducing Delays in Multi-Agent Path Finding

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Multi-Agent Path Finding (MAPF) is a fundamental motion coordination problem arising in multi-agent systems with a wide range of applications. The problem's intractability has led to extensive research on improving the scalability of…

多智能体系统 · 计算机科学 2023-05-26 Tzvika Geft

Executing a multi-agent plan can be challenging when an agent is delayed, because this typically creates conflicts with other agents. So, we need to quickly find a new safe plan. Replanning only the delayed agent often does not yield an…

人工智能 · 计算机科学 2026-04-13 Issa Hanou , Eric Kemmeren , Devin Wild Thomas , Mathijs de Weerdt

Avoiding collisions is the core problem in multi-agent navigation. In decentralized settings, when agents have limited communication and sensory capabilities, collisions are typically avoided in a reactive fashion, relying on local…

多智能体系统 · 计算机科学 2021-07-02 Stepan Dergachev , Konstantin Yakovlev

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…

Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple agents from respective start to goal locations such that no paths conflict. We address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles which…

最优化与控制 · 数学 2024-03-27 Drew Scott , Satyanarayana G. Manyam , David W. Casbeer , Manish Kumar , Isaac E. Weintraub

We propose a novel complete algorithm for multi-agent pathfinding (MAPF) called lazy constraints addition search for MAPF (LaCAM). MAPF is a problem of finding collision-free paths for multiple agents on graphs and is the foundation of…

人工智能 · 计算机科学 2022-11-28 Keisuke Okumura

Multi-Agent Path Finding (MAPF) is an important core problem for many new and emerging industrial applications. Many works appear on this topic each year, and a large number of substantial advancements and performance improvements have been…

人工智能 · 计算机科学 2023-05-16 Bojie Shen , Zhe Chen , Muhammad Aamir Cheema , Daniel D. Harabor , Peter J. Stuckey

In multi-agent path finding (MAPF), the task is to find non-conflicting paths for multiple agents from their initial positions to given individual goal positions. MAPF represents a classical artificial intelligence problem often addressed…

人工智能 · 计算机科学 2021-11-15 Martin Čapek , Pavel Surynek

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…

机器人学 · 计算机科学 2025-10-01 Shaoli Hu , Shizhe Zhao , Zhongqiang Ren

We propose a distributed planning method with asynchronous execution for multi-agent pickup and delivery (MAPD) problems for environments with occasional delays in agents' activities and flexible endpoints. MAPD is a crucial problem…

多智能体系统 · 计算机科学 2023-02-21 Yuki Miyashita , Tomoki Yamauchi , Toshiharu Sugawara

Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when generalizing MAPF methods to real-world scenarios and four…

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…

多智能体系统 · 计算机科学 2026-03-02 He Jiang , Yulun Zhang , Rishi Veerapaneni , Jiaoyang Li

Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem that asks us to plan collision-free paths for a team of cooperative agents. In this work, we show that one of the reasons why MAPF is so hard to solve is due to a…

人工智能 · 计算机科学 2021-03-15 Jiaoyang Li , Daniel Harabor , Peter J. Stuckey , Sven Koenig

Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to agents as soon as they complete their initial targets,…

机器人学 · 计算机科学 2024-04-09 Yimin Tang , Zhenghong Yu , Yi Zheng , T. K. Satish Kumar , Jiaoyang Li , Sven Koenig

We study a novel graph path planning problem for multiple agents that may crash at runtime, and block part of the workspace. In our setting, agents can detect neighboring crashed agents, and change followed paths at runtime. The objective…

机器人学 · 计算机科学 2022-11-28 Keisuke Okumura , Sébastien Tixeuil

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,…

人工智能 · 计算机科学 2020-08-11 Aysu Bogatarkan , Esra Erdem

Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, requiring highly efficient algorithms. Priority Inheritance with Backtracking (PIBT) is a popular…

多智能体系统 · 计算机科学 2026-03-25 Zixiang Jiang , Yulun Zhang , Rishi Veerapaneni , Jiaoyang Li

In multi-agent path finding (MAPF) the task is to navigate agents from their starting positions to given individual goals. The problem takes place in an undirected graph whose vertices represent positions and edges define the topology.…

多智能体系统 · 计算机科学 2019-07-31 Pavel Surynek , T. K. Satish Kumar , Sven Koenig

The multi-agent pathfinding (MAPF) problem seeks collision-free paths for a team of agents from their current positions to their pre-set goals in a known environment, and is an essential problem found at the core of many logistics,…

机器人学 · 计算机科学 2023-10-13 Chengyang He , Tianze Yang , Tanishq Duhan , Yutong Wang , Guillaume Sartoretti

Multi-agent path planning (MAPP) is the problem of planning collision-free trajectories from start to goal locations for a team of agents. This work explores a relatively unexplored setting of MAPP where streams of agents have to go through…

多智能体系统 · 计算机科学 2023-06-30 Kazumi Kasaura , Ryo Yonetani , Mai Nishimura