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Heuristic searchtheory and applications /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Heuristic searchStefan Edelkamp, Stefan Schr�odl.
其他題名:
theory and applications /
作者:
Edelkamp, Stefan.
其他作者:
Schr�odl, Stefan.
出版者:
Amsterdam ;Elsevier/Morgan Kaufmann,c2012.
面頁冊數:
1 online resource (xxiv, 836 p.) :ill.
標題:
Heuristic algorithms.
電子資源:
http://www.sciencedirect.com/science/book/9780123725127
ISBN:
9780123725127 (electronic bk.)
Heuristic searchtheory and applications /
Edelkamp, Stefan.
Heuristic search
theory and applications /[electronic resource] :Stefan Edelkamp, Stefan Schr�odl. - Amsterdam ;Elsevier/Morgan Kaufmann,c2012. - 1 online resource (xxiv, 836 p.) :ill.
Includes bibliographical references and index.
Heuristic search primer. Introduction -- Basic search algorithms -- Dictionary data structures -- Automatically created heuristics -- Heuristic search under memory constraints. Linear-space search -- Memory-restricted search -- Symbolic search -- External search -- Heuristic search under time constraints. Distributed search -- State space pruning -- Real-time search -- Heuristic search variants. Adversary search -- Constraint search -- Selective search -- Heurstic search applications. Action planning -- Automated system verification -- Vehicle navigation -- Computational biology -- Robotics.
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. Provides real-world success stories and case studies for heuristic search algorithms. Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units.
ISBN: 9780123725127 (electronic bk.)
Standard No.: 9786613133953Subjects--Topical Terms:
455932
Heuristic algorithms.
Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: QA76.9.A43 / E34 2012
Dewey Class. No.: 005.1/1
Heuristic searchtheory and applications /
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Heuristic search primer. Introduction -- Basic search algorithms -- Dictionary data structures -- Automatically created heuristics -- Heuristic search under memory constraints. Linear-space search -- Memory-restricted search -- Symbolic search -- External search -- Heuristic search under time constraints. Distributed search -- State space pruning -- Real-time search -- Heuristic search variants. Adversary search -- Constraint search -- Selective search -- Heurstic search applications. Action planning -- Automated system verification -- Vehicle navigation -- Computational biology -- Robotics.
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Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. Provides real-world success stories and case studies for heuristic search algorithms. Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units.
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