Breadth-First Heuristic Search

Recent work shows that the memory requirements of bestfirst heuristic search can be reduced substantially by using a divide-and-conquer method of solution reconstruction. We show that memory requirements can be reduced even further by using a breadth-first instead of a best-first search strategy. We describe optimal and approximate breadth-first heuristic search algorithms that use divide-and-conquer solution reconstruction. Computational results show that they outperform other optimal and approximate heuristic search algorithms in solving domain-independent planning problems.

• Type: Conference
• Year: 2004
• Where: KR
• Authors: Rong Zhou, Eric A. Hansen
• Keywords: Approximate Heuristic Search, Artificial Intelligence, Heuristic Search, Heuristic Search Algorithms, KR 2004