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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Chapter 9 discusses some representational formalisms in which the structure of the representation itself is used to aid retrieval processes and to ... Two examples are semantic networks and the so-called frame-based representations.
Transforming a problem statement into these three components of a production system is often called the representation problem in AI. Usually there are several ways to so represent a problem. Selecting a good representation is one of ...
PROBLEMS OF REPRESENTATION Efficient problem solution requires more than an efficient control strategy. It requires selecting good representations for problem states, moves, and goal conditions. The representation of a problem has a ...
The processes required to represent problems initially and to improve given representations are still poorly understood. It seems that desirable shifts in a problem's representation depend on experience gained in attempts to solve it in ...
This change in representation simply shifts the system description to a lower level. 1.2.2. DECOMPOSABLE PRODUCTION SYSTEMS Commutativity is not the only condition whose fulfillment permits a certain freedom in the order in which rules ...
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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