Multi-agent pathfinding (MAPF) is a well-studied abstract model for navigation in a multi-
robot system, where every robot finds the path to its goal position without any collision. Due …

Abstract Purpose of Review Planning collision-free paths for multiple robots is important for
real-world multi-robot systems and has been studied as an optimization problem on graphs …

Conventional multi-agent path planners typically determine a path that optimizes a single
objective, such as path length. Many applications, however, may require multiple objectives …

Conventional multi-agent path planners typically compute an ensemble of paths while
optimizing a single objective, such as path length. However, many applications may require …

In many real-world applications of multi-agent systems, teams of agents must assign targets
among themselves and plan paths to the targets. The agents must avoid collisions with each …

Abstract In Lifelong Multi-Agent Path Finding (L-MAPF) a team of agents performs a stream
of tasks consisting of multiple locations to be visited by the agents on a shared graph while …

In the multi-agent path finding problem (MAPF) we are given a set of agents each with
respective start and goal positions. The task is to find paths for all agents while avoiding …

We formalize the problem of multi-agent path finding with time windows (MAPF-TW). The
optimization objective is to maximize the average customer satisfaction for all agents when …

We address rule-based algorithms for multi-agent path finding (MAPF). MAPF is a task of
finding non-conflicting paths connecting agents' initial and goal positions in a shared …

多智能体路径搜寻(Multi-agent Path Finding, MAPF) 问题是多智能体系统中的核心基本问题,
被广泛应用于自动化智能仓储, 自动驾驶, 群体机器人等实际场景. 从问题属性来看 …