Articles liés à Combinatorial Search: From Algorithms to Systems
Synopsis
Although they are believed to be unsolvable in general, tractability results suggest that some practical NP-hard problems can be efficiently solved. Combinatorial search algorithms are designed to efficiently explore the usually large solution space of these instances by reducing the search space to feasible regions and using heuristics to efficiently explore these regions. Various mathematical formalisms may be used to express and tackle combinatorial problems, among them the constraint satisfaction problem (CSP) and the propositional satisfiability problem (SAT). These algorithms, or constraint solvers, apply search space reduction through inference techniques, use activity-based heuristics to guide exploration, diversify the searches through frequent restarts, and often learn from their mistakes.
In this book the author focuses on knowledge sharing in combinatorial search, the capacity to generate and exploit meaningful information, such as redundant constraints, heuristic hints, and performance measures, during search, which can dramatically improve the performance of a constraint solver. Information can be shared between multiple constraint solvers simultaneously working on the same instance, or information can help achieve good performance while solving a large set of related instances. In the first case, information sharing has to be performed at the expense of the underlying search effort, since a solver has to stop its main effort to prepare and commu
nicate the information to other solvers; on the other hand, not sharing information can incur a cost for the whole system, with solvers potentially exploring unfeasible spaces discovered by other solvers. In the second case, sharing performance measures can be done with little overhead, and the goal is to be able to tune a constraint solver in relation to the characteristics of a new instance – this corresponds to the selection of the most suitable algorithm for solving a given instance.The book is suitable for researchers, practitioners, and graduate students working in the areas of optimization, search, constraints, and computational complexity.
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À propos de l?auteur
Dr. Youssef Hamadi is the head of the Constraint Reasoning Group at Microsoft Research Cambridge, and his research interests include combinatorial optimization in alternative frameworks (parallel and distributed architectures); the application of machine learning to search; autonomous search; and parallel propositional satisfiability.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Combinatorial Search: From Algorithms to Systems
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ISBN 13 : 9783662514290
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Summarizes the state of the art and proposes a clear architecture for solver and autonomous solversCase studies translate the theoretical ideas into real-world applicationsValuable for researchers and practitioners working on . N° de réf. du vendeur 449137953
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Combinatorial Search: From Algorithms to Systems
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Combinatorial Search: From Algorithms to Systems
Edité par
Springer Berlin Heidelberg, 2016
ISBN 10 : 366251429X
ISBN 13 : 9783662514290
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Although they are believed to be unsolvable in general, tractability results suggest that some practical NP-hard problems can be efficiently solved. Combinatorial search algorithms are designed to efficiently explore the usually large solution space of these instances by reducing the search space to feasible regions and using heuristics to efficiently explore these regions. Various mathematical formalisms may be used to express and tackle combinatorial problems, among them the constraint satisfaction problem (CSP) and the propositional satisfiability problem (SAT). These algorithms, or constraint solvers, apply search space reduction through inference techniques, use activity-based heuristics to guide exploration, diversify the searches through frequent restarts, and often learn from their mistakes.In this book the author focuses on knowledge sharing in combinatorial search, the capacity to generate and exploit meaningful information, such as redundant constraints, heuristic hints, and performance measures, during search, which can dramatically improve the performance of a constraint solver. Information can be shared between multiple constraint solvers simultaneously working on the same instance, or information can help achieve good performance while solving a large set of related instances. In the first case, information sharing has to be performed at the expense of the underlying search effort, since a solver has to stop its main effort to prepare and communicate the information to other solvers; on the other hand, not sharing information can incur a cost for the whole system, with solvers potentially exploring unfeasible spaces discovered by other solvers. In the second case, sharing performance measures can be done with little overhead, and the goal is to be able to tune a constraint solver in relation to the characteristics of a new instance - this corresponds to the selection of the most suitable algorithm for solving a given instance. The book is suitable for researchers, practitioners, and graduate students working in the areas of optimization, search, constraints, and computational complexity. N° de réf. du vendeur 9783662514290
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Combinatorial Search: From Algorithms to Systems
Edité par
Springer Berlin Heidelberg Aug 2016, 2016
ISBN 10 : 366251429X
ISBN 13 : 9783662514290
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Although they are believed to be unsolvable in general, tractability results suggest that some practical NP-hard problems can be efficiently solved. Combinatorial search algorithms are designed to efficiently explore the usually large solution space of these instances by reducing the search space to feasible regions and using heuristics to efficiently explore these regions. Various mathematical formalisms may be used to express and tackle combinatorial problems, among them the constraint satisfaction problem (CSP) and the propositional satisfiability problem (SAT). These algorithms, or constraint solvers, apply search space reduction through inference techniques, use activity-based heuristics to guide exploration, diversify the searches through frequent restarts, and often learn from their mistakes.In this book the author focuses on knowledge sharing in combinatorial search, the capacity to generate and exploit meaningful information, such as redundant constraints, heuristic hints, and performance measures, during search, which can dramatically improve the performance of a constraint solver. Information can be shared between multiple constraint solvers simultaneously working on the same instance, or information can help achieve good performance while solving a large set of related instances. In the first case, information sharing has to be performed at the expense of the underlying search effort, since a solver has to stop its main effort to prepare and communicate the information to other solvers; on the other hand, not sharing information can incur a cost for the whole system, with solvers potentially exploring unfeasible spaces discovered by other solvers. In the second case, sharing performance measures can be done with little overhead, and the goal is to be able to tune a constraint solver in relation to the characteristics of a new instance - this corresponds to the selection of the most suitable algorithm for solving a given instance. The book is suitable for researchers, practitioners, and graduate students working in the areas of optimization, search, constraints, and computational complexity. 156 pp. Englisch. N° de réf. du vendeur 9783662514290
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Combinatorial Search: From Algorithms to Systems
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Combinatorial Search: From Algorithms to Systems
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 2016, 2016
ISBN 10 : 366251429X
ISBN 13 : 9783662514290
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. Neuware -Although they are believed to be unsolvable in general, tractability results suggest that some practical NP-hard problems can be efficiently solved. Combinatorial search algorithms are designed to efficiently explore the usually large solution space of these instances by reducing the search space to feasible regions and using heuristics to efficiently explore these regions. Various mathematical formalisms may be used to express and tackle combinatorial problems, among them the constraint satisfaction problem (CSP) and the propositional satisfiability problem (SAT). These algorithms, or constraint solvers, apply search space reduction through inference techniques, use activity-based heuristics to guide exploration, diversify the searches through frequent restarts, and often learn from their mistakes.In this book the author focuses on knowledge sharing in combinatorial search, the capacity to generate and exploit meaningful information, such as redundant constraints, heuristic hints, and performance measures, during search, which can dramatically improve the performance of a constraint solver. Information can be shared between multiple constraint solvers simultaneously working on the same instance, or information can help achieve good performance while solving a large set of related instances. In the first case, information sharing has to be performed at the expense of the underlying search effort, since a solver has to stop its main effort to prepare and communicate the information to other solvers; on the other hand, not sharing information can incur a cost for the whole system, with solvers potentially exploring unfeasible spaces discovered by other solvers. In the second case, sharing performance measures can be done with little overhead, and the goal is to be able to tune a constraint solver in relation to the characteristics of a new instance ¿ this corresponds to the selection of the most suitable algorithm for solving a given instance.The book is suitable for researchers, practitioners, and graduate students working in the areas of optimization, search, constraints, and computational complexity.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 156 pp. Englisch. N° de réf. du vendeur 9783662514290
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Combinatorial Search : From Algorithms to Systems
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Combinatorial Search: From Algorithms to Systems [Paperback] Hamadi, Youssef (eng)
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Combinatorial Search: From Algorithms to Systems
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ISBN 13 : 9783662514290
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Paperback. Etat : Brand New. reprint edition. 156 pages. 9.30x6.20x0.37 inches. In Stock. N° de réf. du vendeur x-366251429X
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