McGraw-Hill, 1991 - 621 páginas
The breadth of A. I. is explored and explained in this best selling text. Assuming no prior knowledge,it covers topics like neural networks and robotics. This text explores the range of problems which have been and remain to be solved using A. I. tools and techniques. The second half of this text is an excellent reference.
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(0,0) (4,3) (0,0) (1,3) (4,3) (0, 0) (3, 0) Figure 2.6: Two Levels of a Breadth-First
Search Tree (b) For each way that each rule can match the state described in E
do: ... The search procedure we have just described is also called depth-first
Figure 2.7: A Depth-First Search Tree Algorithm: Depth-First Search 1 . If the
initial state is a goal state, quit and return success. 2. Otherwise, do the following
until success or failure is signaled: (a) Generate a successor, £, of the initial state.
Until now, we have really only discussed two systematic control strategies,
breadth-first search and depth-first search (of several varieties). In this section,
we discuss a new method, best-first search, which is a way of combining the
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very poor book for novice.Assumes u already know AI and the language is not at all user friendly.One has to read a sentence repeatedly to get a grasp and some times even then u don't understand.Go for other books much better than this
not soo good to go for novice
What Is Artificial Intelligence?
Problems Problem Spaces and Search
Heuristic Search Techniques
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