Iterative-deepening Bidirectional Heuristic Search with Restricted Memory


  • Shahaf S. Shperberg Ben-Gurion University
  • Steven Danishevski Ben-Gurion University
  • Ariel Felner Ben-Gurion University
  • Nathan R. Sturtevant University of Alberta


Classical Planning Techniques And Analysis


The field of bidirectional heuristic search has recently seen great advances. However, the subject of memory-restricted bidirectional search has not received recent attention. In this paper we introduce a general iterative deepening bidirectional heuristic search algorithm (IDBiHS) that searches simultaneously in both directions while controlling the meeting point of the search frontiers. First, we present the basic variant of IDBiHS, whose memory is linear in the search depth. We then add improvements that exploit consistency and front-to-front heuristics. Next, we move to the case where a fixed amount of memory is available to store nodes during the search and develop two variants of IDBiHS: (1) A*+IDBiHS, that starts with A* and moves to IDBiHS as soon as memory is exhausted. (2) A variant that stores partial forward frontiers until memory is exhausted and then tries to match each of them from the backward side. Finally, we experimentally compare the new algorithms to existing unidirectional and bidirectional ones. In many cases our new algorithms outperform previous ones in both node expansions and time.




How to Cite

Shperberg, S. S., Danishevski, S., Felner, A., & Sturtevant, N. R. (2021). Iterative-deepening Bidirectional Heuristic Search with Restricted Memory. Proceedings of the International Conference on Automated Planning and Scheduling, 31(1), 331-339. Retrieved from