Showing papers on "Best-first search published in 1976"
PARC1
TL;DR: A new algorithm is presented for constructing auxiliary digital search trees to aid in exact-match substring searching that has the same asymptotic running time bound as previously published algorithms, but is more economical in space.
Abstract: A new algorithm is presented for constructing auxiliary digital search trees to aid in exact-match substring searching. This algorithm has the same asymptotic running time bound as previously published algorithms, but is more economical in space. Some implementation considerations are discussed, and new work on the modification of these search trees in response to incremental changes in the strings they index (the update problem) is presented.
1,661 citations
TL;DR: It is shown that the stability observed for heuristic search no longer holds for depth-first search and the “best” and the "worst” heurstic functions are clarified and also discussed is how the heuristic functionh should be modified to obtain a branch-and-bound algorithm with an improved performance.
Abstract: Four known search strategies used in branch-and-bound algorithms-heuristic search, depth-first search, best-bound search, and breadth-first search-are theoretically compared from the viewpoint of the performance of the resulting algorithms. Heuristic search includes the other three as special cases. Since heuristic search is determined by a heuristic functionh, we first investigate how the performance of the resulting algorithms depends onh. In particular, we show that heuristic search is stable in the sense that a slight change inh causes only a slight change in its performance. The “best” and the “worst” heurstic functions are clarified, and also discussed is how the heuristic functionh should be modified to obtain a branch-and-bound algorithm with an improved performance. Finally, properties and limitations of depth-first search, best-bound search, and breadth-first search viewed as special cases of heuristic search are considered. In particular, it is shown that the stability observed for heuristic search no longer holds for depth-first search.
108 citations
TL;DR: It is argued that if search procedures are to use problem-specific information to direct a search, then they must have complete control over the deductive process, which includes the freedom to select any pair of clauses to interact as well as thefreedom to select the literals upon which to attempt the interaction.
Abstract: In, this paper we argue that if search procedures are to use problem-specific information to direct a search, then they must have complete control over the deductive process. This includes the freedom to select any pair of clauses to interact as well as the freedom to select the literals upon which to attempt the interaction. We give examples to indicate the nature of inference rules which are incompatible with such search procedures. We then present a framework for a search procedure to indicate where problem-specific information may be utilized. Finally, we augment the search procedure to prevent the generation of certain redundant inferences. The augmentation makes use of lemmas to avoid replicating deduction sequences in solving multiple instances of the same subproblem at distinct places in the search space.
5 citations
4 citations
07 Jun 1976
TL;DR: The geometric analysis provides an intuitive alternative to the algebraic analysis which appears in the literature and is used to prove some formal properties of heuristic search strategies involving completeness, admissibility, optimality, consistency, and the use of the perfect heuristic.
Abstract: Search spaces for various types of problem representations can be represented in one quadrant of the coordinate planes. This geometric representation is used to prove some formal properties of heuristic search strategies involving completeness, admissibility, optimality, consistency, and the use of the perfect heuristic. The geometric analysis provides an intuitive alternative to the algebraic analysis which appears in the literature.
2 citations
22 Sep 1976
TL;DR: Results of using the algorithm to combine information from the two maps indicate that the success ratio for hitting the target can be improved by a factor of more than two, relative to that expected with random searching.
Abstract: An algorithm for sequentially selecting the coordinates of single candidate exploration sites has been designed with the objective of reducing the fraction of search areas abandoned with undetected targets. Developing and testing the algorithm via an interactive APL-SV system in a CMS environment permitted the off-line printing of maps depicting the search area at various stages of simulated exploration. As a basis for the search strategy, two function surfaces were defined and described by values on a regular grid covering the area. One of these surfaces representing an information map was designed to provide estimates of the uncertainty with which the outcome of each exploration could be predicted. The second surface representing a proximity map provides a numerical measure of the geographic nearness of candidate locations to previously sampled points. Both the information, and proximity maps are updated each time new information becomes available. Results of using the algorithm to combine information from the two maps indicate that the success ratio for hitting the target can be improved by a factor of more than two, relative to that expected with random searching.