Third edition now available

  • You can order a copy (and instructors can request an examination copy) from Cambridge University Press or your local bookstore or Amazon.
  • The full text is now freely available with stable links. See the Complete Book tab above.
  • See endorsements from top AI researchers
  • The first and second editions are still available.
  • What's new:
    • New chapters on deep learning, causality, and social impact
    • Fully revised throughout
    • Social impact sections in each chapter give students context on ethical and societal impacts of AI
    • More content on modern machine learning, giving students a greater understanding of one of the key tools in modern AI
    • Closer integration with AIPython -- open-source runnable pseudocode (in Python) for the algorithms in the book. Designed to be readable and modifiable, AIPython allows students to experiment with and modify the code. It also includes some GUIs to explain running code.

Artificial Intelligence: Foundations of Computational Agents, 3rd edition by David L. Poole and Alan K. Mackworth, Cambridge University Press 2023, is a book about the science of artificial intelligence (AI). It presents artificial intelligence as the study of the design of intelligent computational agents. The book is structured as a textbook, but it is accessible to a wide audience of professionals and researchers. In the last decades we have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This book provides an accessible synthesis of the field aimed at undergraduate and graduate students. It provides a coherent vision of the foundations of the field as it is today. It aims to provide that synthesis as an integrated science, in terms of a multi-dimensional design space that has been partially explored. As with any science worth its salt, artificial intelligence has a coherent, formal theory and a rambunctious experimental wing. The book balances theory and experiment, showing how to link them intimately together. It develops the science of AI together with its engineering applications.

  • The complete book is available online. This html will be stable and will only change when errors are found.
  • We have many online learning resources for many of the topics of this book. The book is closely coordinated with AIPython: Python implementations of the pseudo-code in the book, designed to be as close to the pseudo-code as possible and able to be experimented with.
  • Slides are available for teaching.
  • We have a list of errata from the first printing.
  • Instructors can get a (partial) solution manual and sources for the slides from the instructor resources at Cambridge University Press (see CUP FAQ for access instructions). The slides sources use the LaTeX beamer class and include all figures (in pdf), and hundreds of clicker questions. We plan to release new versions every April, August and December for the foreseeable future.

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Endorsements

  • This is an important textbook. Based on their broad experience, the authors harmonize some of the most exciting recent developments in the field, such as generative AI, with more traditional methods, within a unified agent framework. This will broaden the perspective of those relatively new to the field, for whom AI and deep learning appear almost synonymous.
    • -- Yoav Shoham - Stanford University and AI21 Labs
  • This book is a tour de force. It provides a comprehensive introduction to so many topics in modern AI. The clarity of the exposition and the ability to capture the intuition underlying complex concepts make this book compelling and appealing to a broad audience.
    • -- Pascal Van Hentenryck - Georgia Institute of Technology
  • This new edition offers an up-to-date account of AI, presenting the field in an accessible and unified manner. I particularly like the "relations-late" approach, in which first-order logic and relational AI are covered later, after thoroughly covering more basic, feature-based methods. The hybrid data-driven/model-based approach to agent design that the authors propose will be essential to the development of reliable and trustworthy intelligent systems.
    • -- Kevin Patrick Murphy - Google Brain, author of Probabilistic Machine Learning
  • Poole and Mackworth's now classic textbook has guided my senior undergraduate AI class since its first edition. Coupled with online resources, the book presents a comprehensive overview, with technical substance and many pointers for further study, in a coherent structure that fosters learning of key interrelated concepts. The third edition updates the content to cover the massive recent AI advances.
    • -- Jesse Hoey - University of Waterloo
  • Machine learning has undergone spectacular advances over the last few years, but to harvest the new capabilities one needs an engineering framework to build computational agents. This book teaches students about the concepts and techniques that make that possible.
    • -- Rodney Brooks - MIT and Robust AI
  • Wide-ranging, well-organized, up-to-date, and in-depth coverage of the AI world. The numerous figures, algorithms, and extensive references make this a valuable resource that readers will return to repeatedly. Instructors and students will benefit from the well-crafted end-of-chapter exercises. The thought-provoking social impact sections in each chapter and the social impact chapter admirably address the positive and harmful impacts on people. These complement the strong technical descriptions, wisely encouraging researchers and practitioners to limit the risks by highlighting human-centred AI. Poole and Mackworth are highly acclaimed experts who eagerly present their subject with enthusiasm and thoroughness.
    • -- Ben Shneiderman - University of Maryland, author of Human-Centered AI
  • This revised and extended edition of Artificial Intelligence: Foundations of Computational Agents should become the standard text of AI education. Computer science students will find in this volume a broad and uniquely coherent perspective on many computational models of learning, reasoning, and decision-making. Students of causal inference, in particular, will rejoice at viewing the causal revolution reconnected to its roots in formal logic and probabilistic decision-making, strengthened and reinforced by concrete algorithms, challenging exercises, and open source AIPython codes. Highly recommended.
    • -- Judea Pearl - UCLA, Turing Award winner and author of Causality and The Book of Why
  • This textbook is impressively comprehensive, covering all the major AI paradigms that have been introduced and studied over the years. At the same time, it is up to date with the latest technical advances and interdisciplinary perspectives on social impacts. I expect it to be a valuable resource for both teachers and students.
    • -- Peter Stone - University of Texas at Austin
  • Artificial Intelligence: Foundations of Computational Agents is a great AI textbook written by prominent leaders in the field. It covers everything you want to know about AI in a very accessible style, accompanied by a wide range of thoughtful and challenging exercises. I find this book to be an extremely valuable resource, not only for teaching, but even more so for offering an updated reference to a wide spectrum of foundational subjects at the current frontier of AI.
    • -- Rina Dechter - University of California Irvine, author of Constraint Programming
  • Poole and Mackworth's book has been my go-to resource for students who need an introduction to Artificial Intelligence. While the previous versions have provided a complete overview of the field, the newer version organizes this information in a crystal clear manner. The division of the topics based on what the agent knows, what is in the world, and what the effects of its actions are allow for a logical flow of topics inside AI. As a comprehensive textbook for AI that includes slides, solutions, and code, this book is a must-have on the bookshelf for AI instructors, students, researchers, and practitioners.
    • -- Sriraam Natarajan - University of Texas at Dallas
  • This is a great foundational book on the science of AI, covering the main concepts and techniques using a simple structured approach. The extensive material on the social impact of AI provides much needed attention to the responsible design and use of AI. AI researchers can find here the indispensable foundational knowledge and the needed ethical attitude to create beneficial AI innovation.
    • -- Francesca Rossi - IBM Fellow
  • The latest edition of Poole and Mackworth's book emphasizes the societal impacts of AI in every chapter, making it an essential read for anyone interested in AI, especially those who will shape its future to ensure these powerful technologies benefit society and minimize harms.
    • -- Saleema Amershi - Microsoft Research
  • This textbook provides an amazing introduction to the field of AI. By bringing together learning, reasoning, and decision-making, it shows the rich interconnections across the various AI subfields. The writing is just at the right level to introduce students to the different facets of AI. The updated edition seamlessly integrates the exciting developments in deep learning into the broader AI context. The text also highlights the societal impact of AI, including AI ethics and computational sustainability.
    • -- Carla Gomes - Cornell University
  • Poole and Mackworth - two pioneers of AI - present an admirably broad and complete introduction to the field, with a very useful focus on intelligent agents. From deep learning to causal reasoning, from Bayesian networks to knowledge graphs, from fundamental algorithms to effective heuristics, this book covers a wide range of important topics, each accompanied by a timely section on social impact. Highly recommended!
    • -- Holger Hoos - RWTH Aachen
  • Poole and Mackworth's Artificial Intelligence: Foundations of Computational Agents 3e is a tour de force. This is a comprehensive and clearly written text that takes the reader through core concepts in symbolic AI and machine learning, providing pathways for broad introductory undergraduate courses, or focused graduate courses. It's an outstanding resource for student and instructor alike. Whether you're a seasoned AI researcher or a student entering the field, you'll learn a great deal from reading this book.
    • -- Sheila McIlraith - University of Toronto
  • An outstanding and lucid blast of fresh air, in a world that has lost contact with what AI should be about.
    • -- Gary Marcus - NYU, author of Rebooting AI
  • Artificial Intelligence: Foundations of Computational Agents skillfully delivers a comprehensive exploration of AI ideas, demonstrating exceptional organization and clarity of presentation. Navigating the broad arc of important concepts and methods in AI, the book covers essential technical topics, historical context, and the growing importance of the societal influences of AI, making it an outstanding primary text for students and educators, and a valuable reference for professionals.
    • -- Eric Horvitz - Technical Fellow and Chief Scientific Officer, Microsoft