Recent advancements in bidirectional heuristic search have yielded significant theoretical insights and novel algorithms. While most previous work has concentrated on optimal search methods, this paper focuses on bounded-suboptimal bidirectional search, where a bound on the suboptimality of the solution cost is specified. We build upon the state-of-the-art optimal bidirectional search algorithm, BAE*, designed for consistent heuristics, and introduce several variants of BAE* specifically tailored for the bounded-suboptimal context. Through experimental evaluation, we compare the performance of these new variants against other bounded-suboptimal bidirectional algorithms as well as the standard weighted A* algorithm. Our results demonstrate that each algorithm excels under distinct conditions, highlighting the strengths and weaknesses of each approach.

翻译：近年来，双向启发式搜索领域取得了显著的理论突破与算法创新。尽管先前的研究多集中于最优搜索方法，本文聚焦于有界次优双向搜索，即指定解成本的次优性界限。我们以当前最先进的最优双向搜索算法BAE*（基于一致启发式设计）为基础，提出了若干专门针对有界次优场景的BAE*变体。通过实验评估，我们将这些新变体与其他有界次优双向算法以及标准加权A*算法的性能进行了比较。结果表明，每种算法在不同条件下均表现出独特优势，揭示了各方法的强项与局限性。