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

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 2) RTBS is more efficient than real-time unidirectional search for 15-and 24-puzzles but not for randomly generated mazes. It is 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.