Principles of Artificial Intelligence
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.
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... existentially quantified variable by a Skolem function whose arguments are those universally quantified variables that are bound by universal quantifiers whose scopes include the scope of the existential quantifier being eliminated ...
... existentially quantified variables , and finding values or instances for these variables . That is , we might want to know if a wff such as ( 3x ) W ( x ) , logically follows from S , and if it does , we want an instance of the " x ...
... existentially quantified variable x in the goal wff , and f ( g ( x ) ) taking the place of the existentially quantified variable y in the goal wff - but , in this example , there is the extra disjunct [ B ( h ( x ) ) ^ C ( h ( x ) ...
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