A heuristic search algorithm with modifiable estimate
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Heuristics: intelligent search strategies for computer problem solving
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Three approaches to heuristic search in networks
Journal of the ACM (JACM)
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Artificial Intelligence
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Network search algorithms with modifiable heuristics
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ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
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ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Linear-space best-first search
Artificial Intelligence
Search Algorithms Under Different Kinds of Heuristics—A Comparative Study
Journal of the ACM (JACM)
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EPIA '97 Proceedings of the 8th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
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SBIA '96 Proceedings of the 13th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
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Dynamic improvements of heuristic evaluations during search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Search Heuristics for Box Decomposition Methods
Journal of Global Optimization
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We propose a formal generalization for various works dealing with Heuristic Search in State Graphs. This generalization focuses on the properties of the evaluation functions, on the characteristics of the state graphs, on the notion of path length, on the procedures that control the node expansions, on the rules that govern the update operations. Consequently, we present the algorithm family ϱ and the sub-family Ã, which include Nilsson‘s A or A^* and many of their successors such as HPA, B, A^*_&egr;, A_&egr;, C, BF^*, B′, IDA^*, D, A^**, SDW. We prove general theorems about the completeness and the sub-admissibility that widely extend the previous results and provide a theoretical support for using diverse kinds of Heuristic Search algorithms in enlarged contexts, specially when the state graphs and the evaluation functions are less constrained than ordinarily.