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
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... goal expressions , and resolution between an assertion and a goal . The forward system described in the last section ... expression . We eliminate⇒ symbols , move negation symbols in , Skolemize universal variables , and drop ...
... goal expressions into subgoal expressions . One strategy is to use B - rules that are based on the F - rules that we ... expression contains a literal , L , that unifies with one of the literals in the add list of an F - rule , then we ...
... goal expression is CLEAR ( A ) . Two F - rules have CLEAR on their add list . Let's consider unstack ( x , y ) . As a B - rule , the mgu is { A / y } , and the subgoal expression created is [ HANDEMPTY ^ CLEAR ( x ) ^ ON ( x , A ) ...
Contents
PROLOGUE | 1 |
PRODUCTION Systems and AI | 17 |
SEARCH Strategies FOR | 53 |
Copyright | |
10 other sections not shown