Principles of Artificial Intelligence
A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.
Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
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... errorful solution to a programming or robot control problem and then ... one of finding a minimum cost path over the edges of a graph containing n nodes ...
Various kinds of graph structures and graph searching procedures are used in this ... then it would have the puzzle's solution built into it and, if so, ...
A rule is selected, and if it doesn't lead to a solution, the intervening steps are “forgotten,” and another rule is selected instead. ... Graph Search.
Suppose we decide to use a graph-search control regime in solving the ... PROBLEMS OF REPRESENTATION Efficient problem solution requires more than an ...
Any trip proposed as a solution must be of minimal distance. Figure 1.6 shows part of the search tree that might be generated by a graph-search control ...
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CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4 THE PREDICATE CALCULUS IN AI
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS