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Artificial Intelligence
This is an eagerly awaited revision of the single bestselling introduction to Artificial Intelligence ever published. It retains the best features of the earlier works including superior readability, currency, and excellence in the selection of the examples.
737 pages, Paperback
Published May 10, 1992
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Displaying 1 - 6 of 6 reviews
January 13, 2021
Basically this book helped me to understand on a deeper sense what kind of Algorithms are employed within Artificial Intelligence.I have not finished to read at all. But , now I grasp some concepts written on this book.
I will keep reading this book further, from one time to another.
I will keep reading this book further, from one time to another.
September 17, 2016
Hands down the best introductory book on machine intelligence.
February 1, 2021
Used as supplementary material for amazing AI course by prof. Winston.
December 11, 2019
Read as a text book for AI.
January 23, 2017
i like Mr patrick winston .. he can simplify the problems and theorems to becom so easy ..
Did Not Finish
December 19, 2018DNF at about halfway, and won't review, since - meh - it was fine. I used it during my first Georgia Tech OMSCS course, Knowledge-Based Artificial Intelligence, and that's over now, so... :shrug:
I mean, I love Winston's MIT AI lectures. They are MIND BLOWINGLY good. Here they are. This book is less about "optimal" AI (in the style of neural nets and machine learning) and more about "human-like" AI (in the style of mimicking cognitive systems and encoding semantic relationships). Which I find inherently confusing and kind of gratingly dull. ML is more exciting! And seems to make more "sense" (even if it's less interpretable, often). As such, this book feels like a textbook from history - from a field that has changed quite a lot since it was published.
I mean, I love Winston's MIT AI lectures. They are MIND BLOWINGLY good. Here they are. This book is less about "optimal" AI (in the style of neural nets and machine learning) and more about "human-like" AI (in the style of mimicking cognitive systems and encoding semantic relationships). Which I find inherently confusing and kind of gratingly dull. ML is more exciting! And seems to make more "sense" (even if it's less interpretable, often). As such, this book feels like a textbook from history - from a field that has changed quite a lot since it was published.
Displaying 1 - 6 of 6 reviews





