Artificial Intelligence Foundations of Computational Agents

Artificial Intelligence Foundations of Computational Agents by David L. Poole is a comprehensive guide published by Cambridge University Press on July 13, 2023. This third edition spans 900 pages and is presented in English, making it accessible to a wide range of readers, including junior to senior undergraduates and graduate students. The book offers an in-depth exploration of artificial intelligence, focusing on the design of intelligent computational agents within a coherent framework.
Readers will find that this edition includes significant updates, particularly in the areas of machine learning and natural language processing. The text simplifies complex concepts and provides intuitive explanations and exercises, making it suitable for both academic and professional audiences. Additionally, the book addresses the social and ethical implications of AI and machine learning, balancing theoretical insights with practical applications. Enhanced by strong pedagogical features and online resources, this edition aims to facilitate student comprehension and support independent learning.
Official synopsis Publisher
The second edition of Artificial Intelligence provides a comprehensible and thorough guide for junior to senior undergraduates and graduate students. Updates include a major expansion on machine learning, inclusion of more intuitive explanations and exercises, and simplification of parts that were considered difficult in the first edition. 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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