Heuristic Search: Theory and Applications
Heuristic Search: Theory and Applications
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发表时间：
2011-05
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通讯作者：
S. Edelkamp;Stefan Schrödl;Sven Koenig
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作者：
S. Edelkamp;Stefan Schrödl;Sven Koenig
搜索从一开始就作为解决问题的核心技术对人工智能至关重要。作者给出了启发式搜索的全面概述，并在理论分析与有效实现和应用于现实世界问题之间的讨论之间取得了平衡。详细介绍了当前在搜索方面的发展，如图形数据库和有效利用外部存储器以及主板和图形卡上的并行处理单元的搜索。启发式搜索作为一种解决问题的工具，在解谜、游戏、约束满足和机器学习等应用中得到了展示。虽然不需要以前熟悉启发式搜索，但读者应该对算法、数据结构和微积分有基本的了解。真实世界的案例研究和章节结尾练习有助于创建一幅完整的、实现的图景，说明搜索如何适应人工智能和我们周围的世界。本书提供了启发式搜索算法的实际成功案例和案例研究。它包括许多教科书中尚未涉及的人工智能发展，如模式数据库、符号搜索和并行处理单元。
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. This title provides real-world success stories and case studies for heuristic search algorithms. It includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units.