Kishimoto, Akihiro; Fukunaga, Alex; Botea, Adi
Large-scale, parallel clusters composed of commodity processors are increasingly available, enabling the use of vast processing capabilities and distributed RAM to solve hard search problems. We investigate parallel algorithms for optimal sequential planning, with an emphasis on exploiting distributed memory computing clusters. In particular, we focus on an approach which distributes and schedules work among processors based on a hash function of the search state. We use this approach to...[Show more]
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