Abstract
Pattern databases enable difficult search problems to be solved very quickly, but are large and time-consuming to build. They are therefore best suited to situations where many problem instances are to be solved, and less than ideal when only a few instances are to be solved. This paper examines a technique – hierarchical heuristic search - especially designed for the latter situation. The key idea is to compute, on demand, only those pattern database entries needed to solve a given problem instance. Our experiments show that Hierarchical IDA* can solve individual problems very quickly, up to two orders of magnitude faster than the time required to build an entire high-performance pattern database.
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Holte, R.C., Grajkowski, J., Tanner, B. (2005). Hierarchical Heuristic Search Revisited. In: Zucker, JD., Saitta, L. (eds) Abstraction, Reformulation and Approximation. SARA 2005. Lecture Notes in Computer Science(), vol 3607. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527862_9
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DOI: https://doi.org/10.1007/11527862_9
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