Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Coherent cooperation among communicating problem solvers
IEEE Transactions on Computers
BS*: an admissible bidirectional staged heuristic search algorithm
Artificial Intelligence
Artificial Intelligence
Representing and using organizational knowledge in DAI systems
Distributed artificial intelligence: vol. 2
The trailblazer search: a new method for searching and capturing moving targets
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
An Improved Bidirectional Heuristic Search Algorithm
Journal of the ACM (JACM)
Bidirectional Heuristic Search Again
Journal of the ACM (JACM)
Organization Self-Design of Distributed Production Systems
IEEE Transactions on Knowledge and Data Engineering
Moving-Target Search: A Real-Time Search for Changing Goals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Search for Autonomous Agents and Multiagent Systems
Autonomous Agents and Multi-Agent Systems
Improving efficiency of procedures for compositional synthesis by using bidirectional search
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
RTTES: Real-time search in dynamic environments
Applied Intelligence
Improving the learning efficiencies of realtime search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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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.