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Artificial Intelligence : Foundations of Computational Agents by Alan K. Mackworth and David L. Poole (2023, Hardcover)

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About this product

Product Identifiers

PublisherCambridge University Press

ISBN-101009258192

ISBN-139781009258197

eBay Product ID (ePID)18059033906

Product Key Features

Number of Pages900 Pages

Publication NameArtificial Intelligence : Foundations of Computational Agents

LanguageEnglish

SubjectNatural Language Processing

Publication Year2023

FeaturesRevised

TypeTextbook

Subject AreaComputers

AuthorAlan K. Mackworth, David L. Poole

FormatHardcover

Dimensions

Item Height1.7 in

Item Length10.2 in

Item Width7.2 in

Additional Product Features

Edition Number3

LCCN2023-042160

Dewey Edition22

Reviews'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

IllustratedYes

Dewey Decimal006.3

Edition DescriptionRevised edition

Table Of ContentPreface; Part I. Agents in the World: 1. Artificial intelligence and agents; 2. Agent architectures and hierarchical control; Part II. Reasoning and Planning with Certainty: 3. Searching for solutions; 4. Reasoning with constraints; 5. Propositions and inference; 6. Deterministic planning; Part III. Learning and Reasoning with Uncertainty: 7. Supervised machine learning; 8. Neural networks and deep learning; 9. Reasoning with uncertainty; 10. Learning with uncertainty; 11. Causality; Part IV. Planning and Acting with Uncertainty; 12. Planning with uncertainty; 13. Reinforcement learning; 14. Multiagent systems; Part V. Representing Individuals and Relations: 15. Individuals and relations; 16. Knowledge graphs and ontologies; 17. Relational learning and probabilistic reasoning; Part VI. The Big Picture: 18. The social impact of artificial intelligence; 19. Retrospect and prospect; Appendices; References; Index of Algorithms; Index.

SynopsisFully revised and updated, this comprehensive new edition covers modern AI and machine learning for undergraduate and graduate students. Includes new chapters on deep learning including generative AI, causality and social impact, new social impact sections, major revisions to knowledge graphs, reasoning and decision making, and more AIPython code., 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.

LC Classification NumberQ342.P66 2023