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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Procedure PRODUCTION 1 DATA - initial database 2 until DATA satisfies the termination condition, do: 3 begin 4 select some rule, R, in the set of rules that can be applied to DATA 5 DATA - result of applying R to DATA 6 end 1.1.3.
Should subsequent computation encounter difficulty in producing a solution, the state of the computation reverts to the previous backtracking point, where another rule is applied instead, and the process continues.
For example, suppose the goal state is 1 2 3 74 86 5 and the initial state is 1 2 5 74 86 3 Any applicable rule applied to the initial state description lowers the value of our hill-climbing function. In this case the initial state ...
Backing up will occur (a) whenever we generate a state description that already occurs on the path back to the initial state description, (b) whenever we have applied an arbitrarily set number of rules without having generated a goal ...
4 7| 5 (5) # | | # 4 7|5 | # # : 6 (3) 8 2 1 Q) 8 2 7|5 7 : 6 4 7|5 Again, we have applied six rules without reaching a goal, SO, etc. This state occurs on the path back to the initial state, so we retract the last move and apply “move ...
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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