Principles of Artificial Intelligence
Morgan Kaufmann, Jun 28, 2014 - Computers - 476 pages
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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An abstract understanding of the basic ideas should facilitate understanding specific AI systems (including strengths and weaknesses) and should also prove a sound basis for designing new systems. AI has also embraced the larger ...
Not only does it require the ability to make deductions from hypotheses but demands intuitive skills such as guessing about which lemmas should be proved first in order to help prove the main theorem. A skilled mathematician uses what ...
But if the control system were to maintain this record, then, should a path through DB4 ultimately prove futile, it could resume work immediately from either DB2 or DB3. In order to achieve this sort of flexibility, a control system ...
We prove this result using induction on the depth of a node in the A2 search tree at termination. First, we prove that if A2 expands a node n having zero depth in its search tree, then so will A1. But, in this case, n = s.
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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