Parallelization of non-admissible search algorithms such as GBFS poses a challenge because straightforward parallelization can result in search behavior which significantly deviates from sequential search. Previous work proposed PUHF, a parallel search algorithm which is constrained to only expand states that can be expanded by some tie-breaking strategy for GBFS. We show that despite this constraint, the number of states expanded by PUHF is not bounded by a constant multiple of the number of states expanded by sequential GBFS with the worst-case tie-breaking strategy. We propose and experimentally evaluate One Bench At a Time (OBAT), a parallel greedy search which guarantees that the number of states expanded is within a constant factor of the number of states expanded by sequential GBFS with some tie-breaking policy.

翻译：非可采纳搜索算法（如GBFS）的并行化面临挑战，因为简单的并行化可能导致搜索行为显著偏离顺序搜索。先前的研究提出了PUHF算法，该并行搜索算法被约束为仅扩展那些可通过GBFS的某种平局决胜策略扩展的状态。我们证明，尽管存在此约束，PUHF扩展的状态数量并不受顺序GBFS在最坏情况平局决胜策略下扩展状态数量的常数倍限制。我们提出并实验评估了"一次一个分支"（OBAT）算法，这是一种并行贪婪搜索方法，其保证扩展的状态数量在顺序GBFS采用某种平局决胜策略时扩展状态数量的常数因子范围内。