• Title Artificial Intelligence: Foundations of Computational Agents, 2nd Edition
• Author(s) David L. Poole (Author),‎ Alan K. Mackworth (Author)
• Publisher: Cambridge University Press; 2 edition (September 25, 2017)
• License(s): This online version is free to view and download for personal use only
• Hardcover 820 pages
• eBook HTML
• Language: English
• ISBN-10: 110719539X
• ISBN-13: 978-1107195394
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Book Description

This text is a modern and coherent introduction to the field of Artificial Intelligence that uses rational computational agents and logic as unifying threads in this vast field. Many fully worked out examples, a good collection of paper-and-pencil exercises at various levels of difficulty, programming assignments based on the custom-designed declarative AILog language, and well-integrated online support through the AISpace applets complement the presentation.

Artificial intelligence, including machine learning, has emerged as a transformational science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents presents AI using a coherent framework to study the design of intelligent computational agents.

By showing how the basic approaches fit into a multidimensional design space, readers learn the fundamentals without losing sight of the bigger picture. The new edition also features expanded coverage on machine learning material, as well as on the social and ethical consequences of AI and ML. The book balances theory and experiment, showing how to link them together, and develops the science of AI together with its engineering applications.

Although structured as an undergraduate and graduate textbook, the book's straightforward, self-contained style will also appeal to an audience of professionals, researchers, and independent learners. The second edition is well-supported by strong pedagogical features and online resources to enhance student comprehension.

• David L. Poole is a Professor of Computer Science at the University of British Columbia. He is a co-author of three artificial intelligence books including Statistical Relational Artificial Intelligence: Logic, Probability, and Computation (2016). He is a former Chair of the Association for Uncertainty in Artificial Intelligence, the winner of the Canadian AI Association (CAIAC) 2013 Lifetime Achievement Award, and a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and CAIAC.

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