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.
From inside the book
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Bibliographical and Historical Remarks 267 Exercises 270 CHAPTER 7: BASIC PLAN-GENERATING SYSTEMS 275 Robot Problem Solving 275 A Forward Production System 281 A Representation for Plans 282 A Backward Production System 287 STRIPS 298 ...
... DCOMP 333 Amending Plans 342 Hierarchical Planning 349 Bibliographical and Historical Remarks 357 Exercises 358 STRUCTURED OBJECT REPRESENTATIONS 361 From Predicate Calculus to Units 362 A Graphical Representation: Semantic Networks ...
... and structured-object representations. One of the goals of this book is to fill a gap between theory and practice. AI theoreticians have little difficulty in communicating with each other; this book is not intended to contribute to ...
Example items in such a database might be representations for such facts as “Joe Smith works in the Purchasing Department ... have been developed to enable the efficient representation, storage, and retrieval of large numbers of facts.
The point of the whole perception process is to produce a condensed representation to substitute for the unmanageably immense, raw input data. Obviously, the nature and quality of the final representation depend on the goals of the ...
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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