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Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: booksXpress, Bayonne, NJ, U.S.A.
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Soft Cover. Condition: new.
Published by Springer, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: booksXpress, Bayonne, NJ, U.S.A.
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Hardcover. Condition: new.
Published by Springer, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: BMV Bloor, Toronto, ON, Canada
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Condition: Very Good. Used - Very Good.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Book
Condition: New.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: New.
Published by Springer, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Condition: New.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Published by Springer, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Published by Springer-Verlag New York Inc, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Revaluation Books, Exeter, United Kingdom
Book
Paperback. Condition: Brand New. reprint edition. 156 pages. 9.30x6.20x0.37 inches. In Stock.
Published by Springer Berlin Heidelberg Nov 2013, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Buch. Condition: 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.
Published by Springer Berlin Heidelberg Aug 2016, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: 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.
Published by Springer-Verlag New York Inc, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Revaluation Books, Exeter, United Kingdom
Book
Hardcover. Condition: Brand New. 2013 edition. 139 pages. 9.25x6.25x0.75 inches. In Stock.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: GreatBookPricesUK, Castle Donington, DERBY, United Kingdom
Book
Condition: New.
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Book
Condition: New. This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies. Num Pages: 152 pages, 14 black & white illustrations, 16 colour illustrations, biography. BIC Classification: PBD; PBU; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 8. Weight in Grams: 250. . 2016. Softcover reprint of the original 1st ed. 2013. Paperback. . . . .
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Book
Condition: New. This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies. Num Pages: 139 pages, 14 black & white illustrations, 16 colour illustrations, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 11. Weight in Grams: 403. . 2013. Hardback. . . . .
Published by Springer Berlin Heidelberg, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Buchpark, Trebbin, Germany
Book
Condition: Sehr gut. Zustand: Sehr gut - Buchschnitt verkürzt- gepflegter, sauberer Zustand - Ausgabejahr 2013 | Seiten: 156 | Sprache: Englisch.
Published by Springer Berlin Heidelberg, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book
Buch. Condition: 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.
Published by Springer Berlin Heidelberg, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book
Taschenbuch. Condition: 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.
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Book
Condition: New. This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies. Num Pages: 152 pages, 14 black & white illustrations, 16 colour illustrations, biography. BIC Classification: PBD; PBU; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 8. Weight in Grams: 250. . 2016. Softcover reprint of the original 1st ed. 2013. Paperback. . . . . Books ship from the US and Ireland.
Published by Springer Berlin Heidelberg, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: moluna, Greven, Germany
Book Print on Demand
Condition: 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 .
Published by Springer Berlin Heidelberg, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: moluna, Greven, Germany
Book Print on Demand
Condition: 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 .
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Book
Condition: New. This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies. Num Pages: 139 pages, 14 black & white illustrations, 16 colour illustrations, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 11. Weight in Grams: 403. . 2013. Hardback. . . . . Books ship from the US and Ireland.
Published by Springer 2016-08, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: Chiron Media, Wallingford, United Kingdom
Book
PF. Condition: New.
Published by Springer, 2013
ISBN 10: 3642414818ISBN 13: 9783642414817
Seller: Mispah books, Redhill, SURRE, United Kingdom
Book
Hardcover. Condition: Like New. Like New. book.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: GreatBookPricesUK, Castle Donington, DERBY, United Kingdom
Book
Condition: As New. Unread book in perfect condition.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: dsmbooks, Liverpool, United Kingdom
Book
Paperback. Condition: Like New. Like New. book.
Published by Springer, 2016
ISBN 10: 366251429XISBN 13: 9783662514290
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Book
Condition: As New. Unread book in perfect condition.