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 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 …

Abstract In the Multi-Agent Path Finding (MAPF) problem, a set of agents moving on a graph
must reach their own respective destinations without inter-agent collisions. In practical MAPF …

Abstract Several recently developed Multi-Agent Path Finding (MAPF) solvers scale to large
MAPF instances by searching for MAPF plans on 2 levels: The high-level search resolves …

We consider a variant of the Multi-Agent Path-Finding problem that seeks both task
assignments and collision-free paths for a set of agents navigating on a graph, while …

In this work, we consider the Multi-Agent Pickup-and-Delivery (MAPD) problem, where
agents constantly engage with new tasks and need to plan collision-free paths to execute …

Abstract The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a
large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token …

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 Multi-Agent Path Finding (MAPF) is the planning problem of finding collision-free
paths for a team of agents. We focus on Conflict-Based Search (CBS), a two-level tree …