Descripción del título
Heuristic search [theory an...
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
Monografía
monografia Rebiun18116156 https://catalogo.rebiun.org/rebiun/record/Rebiun18116156 m o d cr mn||||||||| 110803s2012 ne a ob 001 0 eng d 9780123725127 0123725127 9780080919737 0080919731 9780123725127 hardback ; acid-free paper) 0123725127 hardback ; acid-free paper) UPVA 996885058803706 UAM 991007687751204211 UPM 991005521891204212 CBUC 991009628410306719 CBUC 991000732192206712 CBUC 991010367092206709 UCAR 991007809625704213 OPELS. eng. pn. OPELS. OCLCQ. CDX. CGU. OCLCQ. OSU. COO. TEF. OCLCQ. DEBSZ. NT. EBLCP. MHW. E7B. YDXCP. MERUC. OCLCQ. OCLCF. OCLCQ. UNAV 005.1/1 22 Edelkamp, Stefan Heuristic search Recurso electrónico] theory and applications Stefan Edelkamp, Stefan Schrödl Amsterdam Boston Elsevier/Morgan Kaufmann 2012 Amsterdam Boston Amsterdam Boston Elsevier/Morgan Kaufmann xxiv, 836 p. il xxiv, 836 p. EBSCO Academic eBook Collection Complete Incluye referencias bibliográficas e índice 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 Forma de acceso: World Wide Web Schrödl, Stefan