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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Our beliefs ( 1 ) through (4) are inconsistent, so we must choose one for rejection.
... If we reject (2), we also revise our previous underlying belief, however tentative
, that the brother-in- law was telling the truth and Babbitt was in Brooklyn.
One way to state these formulas in English is that the measure of belief in h is 0 if
// is disbelieved with certainty. Otherwise, the measure of belief in h given two
observations is the measure of belief given only one observation plus some ...
Finally, there are stochastic, or randomized algorithms for updating belief
networks. One such algorithm [Chavez, 1989] transforms an arbitrary network into
a Markov chain. The idea is to shield a given node probabilistically from most of
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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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