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
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Artificial intelligence (3rd ed.)
Artificial intelligence (3rd ed.)
Artificial Intelligence
Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Optimal composition of real-time systems
Artificial Intelligence
Anytime Heuristic Searc: First Results TITLE2:
Anytime Heuristic Searc: First Results TITLE2:
The argos image understanding system.
The argos image understanding system.
Constraint-directed search: a case study of job-shop scheduling
Constraint-directed search: a case study of job-shop scheduling
Large-vocabulary speaker-independent continuous speech recognition: the sphinx system
Large-vocabulary speaker-independent continuous speech recognition: the sphinx system
Handbook of data mining and knowledge discovery
Cut-and-solve: an iterative search strategy for combinatorial optimization problems
Artificial Intelligence
Anytime search in dynamic graphs
Artificial Intelligence
Where do we go now?: anytime algorithms for path planning
Proceedings of the 4th International Conference on Foundations of Digital Games
AWA*-a window constrained anytime heuristic search algorithm
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Limited discrepancy beam search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Cut-and-solve: An iterative search strategy for combinatorial optimization problems
Artificial Intelligence
New Approaches to Design and Control of Time Limited Search Algorithms
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Flexible and approximate computation through state-space reduction
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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Beam search executes a state-space search, but may abandon nonpromising search avenues in order to reduce complexity. Although it has existed for more than two decades and has been applied to many real-world problems, beam search still suffers from the drawback of possible termination with no solution or a solution of unsatisfactory quality. In this paper, we first propose a domain-independent heuristic for node pruning, and a method to reduce the possibility that beam search will fail. We then develop a complete beam search algorithm. The new algorithm can not only find an optimal solution, but can also reach better solutions sooner than its underlying search method. We apply complete beam search to the maximum boolean satisfiability and the symmetric and asymmetric Traveling Salesman Problems. Our experimental results show that the domain-independent pruning heuristic is effective and the new algorithm significantly improves the performance of its underlying search algorithm.