Artificial Intelligence

by Patrick Henry Winston

This is the all-time bestselling introduction to artificial intelligence. The third edition retains the best features of the earlier works, including superior readability, currency, and excellence in the selection of examples. Winston emphasizes how artificial intelligence can be viewed from an engineering or a scientific point of view. The new edition offers comprehensive coverage of more material, and many of the ideas presented are enhanced with a variety of side pieces, including application examples such as the Westinghouse nuclear fuel plant optimizer.

Genres: Artificial Intelligence, Computer Science, Science, Technical, Nonfiction, Computers, Technology

460 pages, Hardcover

Published January 1, 1977

Reviews

[Paulina Sierra · Rating 4 out of 5]

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.

[Keith · Rating 5 out of 5]

Hands down the best introductory book on machine intelligence.

[Oleg Dats · Rating 4 out of 5]

Used as supplementary material for amazing AI course by prof. Winston.

[Feroz Dsilva · Rating 5 out of 5]

Read as a text book for AI.

[عين آزال · Rating 5 out of 5]

i like Mr patrick winston .. he can simplify the problems and theorems to becom so easy ..

[briz]

DNF 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.