Heuristic Search: Theory and Applications (Hardcover)
暫譯: 啟發式搜尋:理論與應用(精裝版)
Stefan Edelkamp, Stefan Schroedl
- 出版商: Morgan Kaufmann
- 出版日期: 2011-06-20
- 售價: $3,560
- 貴賓價: 9.5 折 $3,382
- 語言: 英文
- 頁數: 712
- 裝訂: Hardcover
- ISBN: 0123725127
- ISBN-13: 9780123725127
-
相關分類:
人工智慧、Algorithms-data-structures
海外代購書籍(需單獨結帳)
買這商品的人也買了...
-
$875$788 -
$880$695 -
$520$411 -
$580$458 -
$580$452 -
$349$276 -
$360$281 -
$940$700 -
$480$379 -
$650$514 -
$780$616 -
$1,887$1,665 -
$250鳳凰計畫:一個 IT計畫的傳奇故事 (The Phoenix Project : A Novel about IT, DevOps, and Helping your business win)(沙盤特別版)
-
$580$458 -
$520$411 -
$580$452 -
$580$458 -
$1,617Deep Learning (Hardcover)
-
$490$417 -
$590$460 -
$390$308 -
$480$379 -
$580$458 -
$680$537 -
$450$356
商品描述
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
商品描述(中文翻譯)
搜尋自人工智慧的起源以來,一直是解決問題的核心技術。作者提供了啟發式搜尋的全面概述,平衡了理論分析與高效實作及其在現實世界問題中的應用之間的討論。當前搜尋的發展,如模式資料庫以及在主板和顯示卡上有效利用外部記憶體和並行處理單元的搜尋,均有詳細說明。
啟發式搜尋作為解決問題的工具,展示了在拼圖解決、遊戲玩法、約束滿足和機器學習等應用中的實際應用。雖然不需要對啟發式搜尋有先前的熟悉,但讀者應具備基本的演算法、資料結構和微積分知識。現實世界的案例研究和章節結尾的練習題有助於全面了解搜尋如何融入人工智慧的世界以及我們周遭的世界。
*提供啟發式搜尋演算法的現實成功故事和案例研究 *包括許多尚未在教科書中涵蓋的人工智慧發展,如模式資料庫、符號搜尋和並行處理單元