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. |
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... domains of interest in AI typically involves a high-cost control strategy, in terms of the storage and computations required. \ \ Overall cost for the \ \--~ production system 53 CHAPTER 2. SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS.
... domain is used. Those rules that are “guessed,” using the heuristic information, most appropriate for that database occur early in the ordering. The applicable rules can be ordered arbitrarily if no ordering information is available ...
... domain is used in ordering the nodes on OPEN, some arbitrary scheme must be used in step 8 of the algorithm. The resulting search procedure is called uninformed. In AI, we are typically not interested in uninformed procedures, but we ...
... domain. Such information might be similar to that used in the function W(n) in the 8-puzzle example. We call h the heuristic function and will discuss it in more detail later. Suppose we now use as an evaluation function f(n) = g(n) + h ...
... domain. Clearly, using h(n) = 0 reflects complete absence of any heuristic information about the problem, even though such an estimate is a lower bound on h *(n) and therefore leads to an admissible algorithm. Let us compare two ...
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 |