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Artificial Intelligence Structures and Strategies 5th Edition
The most general change for the fifth edition was the extension of the material related to
the stochastic approaches to AI. To accomplish we added a completely new Chapter 5 that introduces the stochastic methodology. From the basic foundations of set theory and
counting we develop the notions of probabilities, random variables, and independence. We present and nse Bayes' theorem first with one symptom and one disease and then in its full general form.
the stochastic approaches to AI. To accomplish we added a completely new Chapter 5 that introduces the stochastic methodology. From the basic foundations of set theory and
counting we develop the notions of probabilities, random variables, and independence. We present and nse Bayes' theorem first with one symptom and one disease and then in its full general form.
We examine the hypotheses that underlie the use of Bayes and then present the argmax and naive Bayes approaches. We present examples of stochastic reasoning, including several from work in the analysis of language phenomena. We also introduce the idea of conditional independence that leads to our presentation of Bayesian belief networks (BBNs) and d-separation in Chapter 9.
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