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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... the first , we present several logical formalisms that provide mechanisms for
performing nonmonotonic reasoning . In the last four , we discuss approaches to
the implementation of such reasoning in problem - solving programs . For more ...
If we know the prior probabilities of finding each of the various minerals and we
know the probabilities that if a mineral is present then certain physical
characteristics will be observed , then we can use Bayes ' formula to compute ,
from the ...
( b ) For each attribute A that is present ( at the top level ) in either G1 or G2 do i .
If A is not present at the top level in the other input , then add A and its value to
NEW . ii . If it is , then call Graph - Unify with the two values for A . If that fails , then
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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
Heuristic Search Techniques
Knowledge Representation Issues
Derechos de autor
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