Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
BS*: an admissible bidirectional staged heuristic search algorithm
Artificial Intelligence
Heuristic search in restricted memory (research note)
Artificial Intelligence
Efficient memory-bounded search methods
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
ITS: an efficient limited-memory heuristic tree search algorithm
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
BIDA: an improved perimeter search algorithm
Artificial Intelligence
An Improved Bidirectional Heuristic Search Algorithm
Journal of the ACM (JACM)
Enhanced Iterative-Deepening Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Searching with Pattern Databases
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
From approximate to optimal solutions: constructing pruning and propagation rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Bidirectional heuristic search reconsidered
Journal of Artificial Intelligence Research
How to use limited memory in heuristic search
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
From approximate to optimal solutions: a case study of number partitioning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Finding optimal solutions to the twenty-four puzzle
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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Recently, we showed that for traditional bidirectional search with "front-to-end" evaluations, it is not the meeting of search fronts but the cost of proving the optimality of a solution that is problematic. Using our improved understanding of the problem, we developed a new approach to improving this kind of search: switching to unidirectional search after the search frontiers meet for the first time (with the first solution found). This new approach shows improvements over previous bidirectional search approaches and (partly) also over the corresponding unidirectional search approaches in different domains. Together with a special-purpose improvement for the TSP, this approach showed better results than the standard search algorithms using the same knowledge.