资源论文Depth-First Memory-Limited AND/OR Search and Unsolvability in Cyclic Search Spaces

Depth-First Memory-Limited AND/OR Search and Unsolvability in Cyclic Search Spaces

2019-09-29 | |  73 |   45 |   0
Abstract Computing cycle-free solutions in cyclic AND/OR search spaces is an important AI problem. Previous work on optimal depth-first search strongly assumes the use of consistent heuristics, the need to keep all examined states in a transposition table, and the existence of solutions. We give a new theoretical analysis under relaxed assumptions where previous results no longer hold. We then present a generic approach to proving unsolvability, and apply it to RBFAOO and BLDFS, two state-of-theart algorithms. We demonstrate the performance in domain-independent nondeterministic planning

上一篇:DeltaDou: Expert-level Doudizhu AI through Self-play

下一篇:Direction-Optimizing Breadth-First Search with External Memory Storage

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...