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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... or difference metrics between an arbitrary node and the goal set have been ... GRAPHSEARCH. By convention, the nodes on OPEN are ordered in increasing order of their f values. Ties among f values are ordered ... GRAPH-SEARCH PROCEDURES.
... and will discuss it in more detail later. Suppose we now use as an ... graph, it always terminates in an optimal path from s to a goal node ... or in step 5. Notice that in every cycle through the loop of the algorithm, a node is removed ...
... and that both A1 and A2 are versions of A*. Suppose that A1 and A2 are used to search an implicit graph having a ... or less, in the A2 search tree. We must now prove that any node n expanded by A2 and of depth k + 1 in 'the A2 search ...
... Or g2(n) + he(n) < f*(s) Or h2(n) < f*(s) – ge(n). Comparing this inequality ... and A2 are two versions of A* such that A2 is more informed than A1, then at the termination of their searches on any graph ... or CLOSED. The search tree may then ...
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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 |