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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That is, f(n) is an estimate of the cost of a minimal cost path constrained to go
through node n. That node on OPEN ... Often we are interested in knowing the
cost k (s,n) of an optimal path from a given start node, s, to some arbitrary node n.
(This path is the lowest cost path from s to n found so far by the search algorithm.
... Let us say that a search algorithm is admissible if, for any graph, it always
terminates in an optimal path from s to a goal node whenever a path from s to a
Next we would like to show that if a path from s to a goal node exists, A* will
terminate even for infinite graphs. ... (Recall that g”(n) is the cost of the optimal
path from s to n, and that g(n) is the cost of the path in the search tree from s to
node n.) ...
But the f* value of any node on an optimal path is equal to f*(s), the minimal cost,
and therefore f(n) < f*(s). Thus, we have: RESULT 2: At any time before A*
terminates, there exists on OPEN a node n' that is on an optimal path from s to a
the least costly paths in G from nodes to the descendants of node n. In addition to
the burden of ... We now show that, given the monotone restriction, when A*
expands a node, it has found an optimal path to that node. Let n be any node ...
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CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4 THE PREDICATE CALCULUS IN AI
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS