Principles of Artificial IntelligenceA 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
Results 6-10 of 73
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 strategy in solving this problem. The numbers next to the edges of the tree are the ...
Suppose we have already represented a problem for solution by a production system. Imagine that this production system has a global database, rules that can modify it, and a graph-search control strategy that generates a search tree of ...
A solution to this rewriting problem can be illustrated by a subgraph of the AND/OR graph. Such a solution subgraph is shown by darkened ... We shall discuss strategies for searching AND/OR graphs to find solution graphs in chapter 3.
Additional references for AND/OR graph methods are given in chapter 3. ... described a system called UNDERSTAND for converting natural language (English) descriptions of problems into representations suitable for problem solution.
Compared with graph-search control regimes, backtracking strategies are typically simpler to implement and ... 2 if DEADEND(DATA), return FAIL; DEADEND is a predicate true for arguments that are known not to be on a path to a solution.
What people are saying - Write a review
Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |