Artificial Intelligence: Foundations of Computational Agents

by David L. Poole, Alan K. Mackworth

Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.

Genres: Computer Science, Artificial Intelligence, Nonfiction, Academic, Textbooks, Technology, Philosophy

900 pages, Hardcover

First published May 30, 2006

Reviews

[Tien Manh · Rating 4 out of 5]

CPSC 322!

[Mehmet Davut · Rating 5 out of 5]

If you don't know anything about the Artificial Intelligence theory and know some linear algebra and probability, this book is great. It makes you understand what is different about programming an Artificial Intelligence application than the traditional applications. I liked the book's theoretical approach while teaching Artificial Intelligence subject, good examples!

Just beware that it doesn't teach how to implement any Artificial Intelligence application, but makes you understand how to build them.