Artificial Intelligence
Strategies, Applications, and Models through SEARCH
2nd Edition
Published on 10. December 1998
Book
Hardback
400 pages
978-1-57958-004-9 (ISBN)
Description
The eleven chapters This text on Artificial Intelligence uses the unifying thread of SEARCH to bring together the major techniques used in symbolic Artificial Intelligence. The authors included program code to illustrate concepts - code is offered in both POP-11 and Prolog. Each chapter covers a technique and are divided into three sections: 1) introduction to the technique; 2) development of a low-level of (POP-11) implementation; 3) development of a high-level (Prolog) implementation. This practical book should be valuable to those experienced in artificial intelligence, students with some programming background, and academics and professionals looking for a concise discussion of artificial intelligence through SEARCH.
More details
Edition
2nd New edition
Language
English
Place of publication
London
United Kingdom
Edition type
New edition
Dimensions
Height: 229 mm
Width: 152 mm
Weight
635 gr
ISBN-13
978-1-57958-004-9 (9781579580049)
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Schweitzer Classification
Content
Search-related techiques in AI: why search; objectives; problem-solving systems; state space search and problem reduction; blind search and heuristic search; graphs and trees; organisation of the book; searching for a solution path in a state space; problem reduction; a very brief comparison of POP-11 and Prolog; further reading. Simple state space search: path-finding; setting up the database; setting up the path-finding function; the generality of search; search spaces and search trees; constructing an explicit representation of the search-tree; search graphs; node terminology; backwards v. forwards searching; OR-tree search in Prolog; reading; exercises. State space search: introduction; the water jugs problem; constructing successor nodes; the problem space; searching for a solution path; problem space exploration strategies; breadth-first search; agendas; implementing depth-first search using an agenda; iterative deepening; water jugs in Prolog; agendas in Prolog; iterative deepening in Prolog; reading; exercises; notes. Heuristic state space search: introduction; the 8-puzzle; constructing 8-puzzle successors; heuristic search; hill-climbing search; heuristic breadth-first search; ordered search and the A* algorithm; heuristic search in Prolog; reading; exercises; notes. Heuristic search of game trees; computing successors in the game of nim; minimax evaluation; worked example; alpha-beta cutoffs; implementing a nim-playing program; minimaxing in Prolog. (Part contents).