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 …

Multi-agent navigation in dynamic environments is of great industrial value when deploying
a large scale fleet of robot to real-world applications. This paper proposes a decentralized …

In the multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple
agents. In this paper we present the first SAT-solver for the sum-of-costs variant of MAPF …

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 …

Abstract Multi-Agent Path Finding (MAPF) is well studied in both AI and robotics. Given a
discretized environment and agents with assigned start and goal locations, MAPF solvers …

Abstract Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents
such that every agent reaches its goal and the agents do not collide. In recent years, there …

Abstract Conflict-Based Search (CBS) and its enhancements are among the strongest
algorithms for Multi-Agent Path Finding. Recent work introduced an admissible heuristic to …

Abstract Multi-Agent Path Finding (MAPF) has been widely studied in the AI community. For
example, Conflict-Based Search (CBS) is a state-of-the-art MAPF algorithm based on a …

Multi-Agent Path Finding (MAPF) is essential to large-scale robotic systems. Recent
methods have applied reinforcement learning (RL) to learn decentralized polices in partially …

Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence that can be
solved quickly in practice when using simplified agent assumptions. However, real-world …