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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.
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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.
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- VerlagSpringer
- Erscheinungsdatum1999
- ISBN 10 0387988327
- ISBN 13 9780387988320
- EinbandTapa dura
- SpracheEnglisch
- Anzahl der Seiten228
- Kontakt zum HerstellerNicht verfügbar
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State-Space Search : Algorithms, Complexity, Extensions, and Applications
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Zustand: Gut. Zustand: Gut | Seiten: 228 | Sprache: Englisch | Produktart: Bücher. Artikel-Nr. 221/203
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STATE-SPACE SEARCH : ALGORITHMS, COMPLEXITY, AND APPLICATIONS
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Hardcover. Octavo, xvi, 201 pages. In Good condition. Spine is silver with brown print. Boards in glossy illustrated paper. Light wear to spine caps, remains of small vendor label on rear. Text block has mark in red ink on bottom edge. Illustrated: b&w graphs, tables, charts. NOTE: Shelved in Netdesk Column G. 1379275. FP New Rockville Stock. Artikel-Nr. 1379275
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State-Space Search: Algorithms, Complexity, Extensions, and Applications
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Zustand: Sehr gut. Auflage: 1999. 201 Seiten ex Library Book / aus einer wissenschafltichen Bibliothek / Sprache: Englisch Gewicht in Gramm: 469 24,1 x 16,1 x 1,6 cm, Gebundene Ausgabe. Artikel-Nr. 370893
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State-Space Search
Verlag:
Springer New York, Springer US Okt 1999, 1999
ISBN 10: 0387988327
ISBN 13: 9780387988320
Neu
Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Buch. Zustand: Neu. 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 228 pp. Englisch. Artikel-Nr. 9780387988320
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State-Space Search : Algorithms, Complexity, Extensions, and Applications
Verlag:
Springer New York, Springer US, 1999
ISBN 10: 0387988327
ISBN 13: 9780387988320
Neu
Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: 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. Artikel-Nr. 9780387988320
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State-Space Search: Algorithms, Complexity, Extensions, and Applications
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