Artificial Intelligence

Front Cover
Cambridge University Press, Sep 25, 2017 - Computers - 792 pages
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.
 

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Contents

Agent Architectures and Hierarchical Control
49
Reasoning Planning and Learning with Certainty
75
Reasoning with Constraints
125
Propositions and Inference
173
Planning with Certainty
239
Supervised Machine Learning
267
Reasoning Learning and Acting with Uncertainty
341
Planning with Uncertainty
425
Learning to Act
549
Reasoning Learning and Acting with Individuals and Rela
579
Ontologies and KnowledgeBased Systems
645
Relational Planning Learning and Probabilistic Reasoning
691
Retrospect and Prospect
731
A Mathematical Preliminaries and Notation
745
References
751
Index
773

Learning with Uncertainty
487
Multiagent Systems
521

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About the author (2017)

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.

Alan K. Mackworth is a Professor of Computer Science at the University of British Columbia. He has authored over 130 papers and co-authored two books: Computational Intelligence: A Logical Approach (1997) and Artificial Intelligence: Foundations of Computational Agents (2010). His awards include the Artificial Intelligence Journal (AIJ) Classic Paper Award and the Association of Constraint Programming (ACP) Award for Research Excellence. He has served as President of the International Joint Conference on Artificial Intelligence (IJCAI), the Association for the Advancement of Artificial Intelligence (AAAI) and the Canadian AI Association (CAIAC). He is a Fellow of AAAI, CAIAC and the Royal Society of Canada.

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