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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Artificial Intelligence for Undergraduate Students provides a comprehensive introduction to AI, blending foundational concepts with practical applications. The book explores the history and foundations of AI, intelligent agents, and their environments, as well as expert systems and chatbots. It delves into uncertainty handling, reasoning with Bayes' rule, and search strategies like A* and greedy best-first search. Knowledge-based agents are covered extensively, including logic, reasoning patterns, and inference methods. With rich visuals (29 figures, 12 tables) and accessible language, this textbook serves as an engaging resource for students embarking on their AI journey, equipping them with the tools to navigate this dynamic field.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Artificial Intelligence for Undergraduate Students provides a comprehensive introduction to AI, blending foundational concepts with practical applications. The book explores the history and foundations of AI, intelligent agents, and their environments, as well as expert systems and chatbots. It delves into uncertainty handling, reasoning with Bayes' rule, and search strategies like A* and greedy best-first search. Knowledge-based agents are covered extensively, including logic, reasoning patterns, and inference methods. With rich visuals (29 figures, 12 tables) and accessible language, this textbook serves as an engaging resource for students embarking on their AI journey, equipping them with the tools to navigate this dynamic field.