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 Multi-Agent Path Finding (MAPF), ie, finding collision-free paths for multiple robots,
is important for many applications where small runtimes are necessary, including the kind of …

The task in the multi-agent path finding problem (MAPF) is to find paths for multiple agents,
each with a different start and goal position, such that agents do not collide. A successful …

The performance of heuristic search-based planners depends heavily on the quality of the
heuristic function used to focus the search. These algorithms work fast and generate high …

Optimal path planning is the problem of finding a valid sequence of states between a start
and goal that optimizes an objective. Informed path planning algorithms order their search …

Path finding in multi-agent systems aims to identify collision-free and cost-optimized paths
for all agents with distinct start and goal positions. It poses challenging optimization …

Heuristic search algorithms, eg A*, are the commonly used tools for pathfinding on grids, ie
graphs of regular structure that are widely employed to represent environments in robotics …

The need for finding a set of plans rather than one has been motivated by a variety of
planning applications. The problem is studied in the context of both diverse and top-k …

Focal search (FS) is a bounded-suboptimal search (BSS) variant of A*. Like A*, it uses an
open list whose states are sorted in increasing order of their f-values. Unlike A*, it also uses …

In a common parking lot, much of the space is devoted not to parking but to lanes in which
cars travel to and from parking spaces. Lanes must not be blocked for one simple reason: a …