Revisiting Immediate Duplicate Detection in External Memory Search


  • Shunji Lin The University of Tokyo
  • Alex Fukunaga The University of Tokyo


Heuristic Search, External Memory Search, Immediate Duplicate Detection, Delayed Duplicate Detection, SSD


External memory search algorithms store the open and closed lists in secondary memory (e.g., hard disks) to augment limited internal memory. To minimize expensive random access in hard disks, these algorithms typically employ delayed duplicate detection (DDD), at the expense of processing more nodes than algorithms using immediate duplicate detection (IDD). Given the recent ubiquity of solid state drives (SSDs), we revisit the use of IDD in external memory search. We propose segmented compression, an improved IDD method that significantly reduces the number of false positive access into secondary memory. We show that A*-IDD, an external search variant of A* that uses segmented compression-based IDD, significantly improves upon previous open-addressing based IDD. We also show that A*-IDD can outperform DDD-based A* on some domains in domain-independent planning.




How to Cite

Lin, S., & Fukunaga, A. (2018). Revisiting Immediate Duplicate Detection in External Memory Search. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from



AAAI Technical Track: Heuristic Search and Optimization