Real-time bidirectional search: Coordinated problem solving in uncertain situations

Toru Ishida*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


This paper investigates real-time bidirectional search (RTBS) algorithms, where two problem solvers, starting from the initial and goal states, physically move toward each other. To evaluate the RTBS performance, two kinds of algorithms are proposed and are compared to real-time unidirectional search. One is called centralized RTBS where a supervisor always selects the best action from all possible moves of the two problem solvers. The other is called decoupled RTBS where no supervisor exists and the two problem solvers independently select their next moves. Experiments on mazes and n-puzzles show that 1) in clear situations decoupled RTBS performs better, while in uncertain situations, centralized RTBS becomes more efficient, and that 2) RTBS is more efficient than real-time unidirectional search for 15-and 24-puzzles but not for randomly generated mazes. It will be shown that the selection of the problem solving organization is the selection of the problem space, which determines the baseline of the organizational efficiency; once a difficult problem space is selected, the local coordination among problem solvers hardly overcome the deficit.

Original languageEnglish
Pages (from-to)617-628
Number of pages12
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number6
Publication statusPublished - 1996
Externally publishedYes


  • Bidirectional search
  • Heuristic depression
  • Organizational problem solving
  • Problem solving
  • Real-time problem solving
  • Real-time search
  • Search

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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