Customer Reviews

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

5 star:		(2)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(1)

 

 

One of the best references on probability theory and uncertain reasoning, this book is one of my most prized. It's lucid enough to be an excellent textbook for the novice, and thorough enough to be a valuable reference for the experienced. It's a book that will always remind me (lest I forget) of the importance of probabilistic reasoning in AI.

I used this text in addtition to a few others for a course in probablistic reasoning (Bayes nets, etc.) and found that it was very unhelpful. The explanations were very poor and many parts were difficult to read. Also, there weren't very many examples and those that were provided were not very detailed. If you're looking for a text to learn probabilistic reasoning I would suggest trying a different book. Pearl's book could be useful as a 2nd or 3rd reference but not for the primary text. 2 thumbs down.

This book is an absolutely essential book for AI programming. I've found no better book for explaining the recent advances in probability theory and its relevance to real-life, practical artificial intelligence development. It's written in a very down-to-earth and highly entertaining style with plenty of examples.

I've been looking for a good introduction to Bayes nets for a long time, and this one is by far the best and most comprehensive.

Probability is increasingly becoming one of the major foundations of effective artificial intelligence, and I strongly recommend this book to anyone with an interest in AI or probability theory.