This book is about problem-solving. In particular it is about heuristic state-space search for combinatorial optimization - one of the fundamental problems of computer science. Written for researchers in computer science, the author presupposes a basic familiarity with complexity theory. In addition, it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions.
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This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory, and it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two successful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions quickly, and the second is forward estimation for constructing more informative evaluation functions.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Condición: Sehr gut. Zustand: Sehr gut | Seiten: 220 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 24220486/2
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory, and it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two successful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions quickly, and the second is forward estimation for constructing more informative evaluation functions. 220 pp. Englisch. Nº de ref. del artículo: 9781461271833
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Librería: Chiron Media, Wallingford, Reino Unido
PF. Condición: New. Nº de ref. del artículo: 6666-IUK-9781461271833
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Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound tec. Nº de ref. del artículo: 4189813
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is about problem solving. Specifically, it is about heuristic state-space search under branch-and-bound framework for solving com binatorial optimization problems. The two central themes of this book are the average-case complexity of heuristic state-space search algorithms based on branch-and-bound, and their applications to developing new problem-solving methods and algorithms. Heuristic state-space search is one of the fundamental problem-solving techniques in Computer Science and Operations Research, and usually constitutes an important component of most intelligent problem-solving systems. The search algorithms considered in this book can be classified into the category of branch-and-bound. Branch-and-bound is a general problem-solving paradigm, and is one of the best techniques for optimally solving computation-intensive problems, such as scheduling and planning. The main search algorithms considered include best-first search, depth first branch-and-bound, iterative deepening, recursive best-first search, and space-bounded best-first search. Best-first search and depth-first branch-and-bound are very well known and have been used extensively in Computer Science and Operations Research. One important feature of depth-first branch-and-bound is that it only requires space this is linear in the maximal search depth, making it very often a favorable search algo rithm over best-first search in practice. Iterative deepening and recursive best-first search are the other two linear-space search algorithms. Iterative deepening is an important algorithm in Artificial Intelligence, and plays an irreplaceable role in building a real-time game-playing program. Nº de ref. del artículo: 9781461271833
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9781461271833_new
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is about problem solving. Specifically, it is about heuristic state-space search under branch-and-bound framework for solving com binatorial optimization problems. The two central themes of this book are the average-case complexity of heuristic state-space search algorithms based on branch-and-bound, and their applications to developing new problem-solving methods and algorithms. Heuristic state-space search is one of the fundamental problem-solving techniques in Computer Science and Operations Research, and usually constitutes an important component of most intelligent problem-solving systems. The search algorithms considered in this book can be classified into the category of branch-and-bound. Branch-and-bound is a general problem-solving paradigm, and is one of the best techniques for optimally solving computation-intensive problems, such as scheduling and planning. The main search algorithms considered include best-first search, depth first branch-and-bound, iterative deepening, recursive best-first search, and space-bounded best-first search. Best-first search and depth-first branch-and-bound are very well known and have been used extensively in Computer Science and Operations Research. One important feature of depth-first branch-and-bound is that it only requires space this is linear in the maximal search depth, making it very often a favorable search algo rithm over best-first search in practice. Iterative deepening and recursive best-first search are the other two linear-space search algorithms. Iterative deepening is an important algorithm in Artificial Intelligence, and plays an irreplaceable role in building a real-time game-playing program.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch. Nº de ref. del artículo: 9781461271833
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 348. Nº de ref. del artículo: C9781461271833
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. 217 pages. 9.25x6.10x0.50 inches. In Stock. Nº de ref. del artículo: x-1461271835
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Condición: New. Nº de ref. del artículo: ABLIING23Mar2716030028613
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