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 …

This volume covers both the art and the technology of game AI. It includes core algorithms
that you'll need to succeed, such as behavior trees, utility theory, spatial representation, path …

Bounded suboptimal search algorithms offer shorter solving times by sacrificing optimality
and instead guaranteeing solution costs within a desired factor of optimal. Typically these …

To harness modern multicore processors, it is imperative to develop parallel versions of
fundamental algorithms. In this paper, we compare different approaches to parallel best-first …

Anytime variants of Dijkstra's and A* shortest path algorithms quickly produce a suboptimal
solution and then improve it over time. For example, ARA* introduces a weighting value" …

We discuss the relationships between three approaches to greedy heuristic search: best-
first, hill-climbing, and beam search. We consider the design decisions within each family …

Suboptimal search algorithms offer shorter solving times by sacrificing guaranteed solution
optimality. While optimal searchalgorithms like A* and IDA* require admissible heuristics …

Motion planners have been recently developed that provide path quality guarantees for
robots with dynamics. This work aims to improve upon their efficiency, while maintaining …

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 …

This paper studies the problem of querying graphs within bounded resources. Given a query
Q, a graph G and a small ratio α, it aims to answer Q in G by accessing only a fraction GQ of …