book artificial intelligence: foundations of computational agents

artificial intelligence: foundations of computational agents book by david l. poole

embark on a comprehensive journey into the core principles of artificial intelligence with artificial intelligence: foundations of computational agents by david l. poole and alan k. mackworth. this seminal work serves as an indispensable guide for anyone seeking to understand the science behind intelligent systems. whether you are a student, researcher, or simply a curious mind, this book provides a clear and accessible synthesis of a rapidly evolving discipline. dive deep into the design of computational agents and explore the intricate balance between theoretical foundations and practical applications.

artificial intelligence: foundations of computational agents summary

this highly acclaimed textbook offers a thorough exploration of artificial intelligence, presenting the field as the study of designing intelligent computational agents. it provides a coherent framework, allowing readers to grasp fundamental concepts by situating various approaches within a multidimensional design space. the latest edition significantly expands upon machine learning, causality, and the social and ethical implications of ai, ensuring a contemporary and relevant perspective. the book adeptly balances theoretical insights with experimental evidence, illustrating how these two crucial aspects of ai are intimately connected. it details the science of ai alongside its engineering applications, making complex topics understandable. the authors approach ensures that readers not only learn the foundational principles but also gain an appreciation for the broader picture and societal impact of ai. furthermore, the integration of pseudocode and open-source python code (aipython) facilitates hands-on experimentation, reinforcing theoretical knowledge with practical application. the books structure progresses logically, building from simpler agent designs to more complex ones, with case studies that bridge theoretical concepts to real-world applications. this approach makes it an invaluable resource for understanding ais current frontier and future potential.

1. full book name: artificial intelligence: foundations of computational agents
2. author name: david l. poole and alan k. mackworth
3. genre: computer science, artificial intelligence, textbooks
4. page count: approximately 682-898 pages depending on edition
5. isbn: 9781009258197 (3rd edition hardback)
6. asin: not explicitly found in search results for recent editions, typical for printed books.
7. edition language: english
8. date of publication: 3rd edition published september 2023 (online august 14, 2023)

about the author david l. poole

david l. poole is a distinguished professor emeritus of computer science at the university of british columbia. he is widely recognized for his significant contributions to artificial intelligence, particularly in areas such as knowledge representation, reasoning under uncertainty, and computational logic. poole is a recipient of the canadian ai association (caiac) lifetime achievement award and is a fellow of both the association for the advancement of artificial intelligence (aaai) and caiac, underscoring his impact on the field.

artificial intelligence: foundations of computational agents faq

1. what is the primary focus of artificial intelligence: foundations of computational agents?

   the book primarily focuses on presenting artificial intelligence as the science of designing intelligent computational agents. it aims to provide a coherent framework for understanding ai, balancing theoretical foundations with practical engineering applications.

2. who is the target audience for this book?

   this textbook is suitable for a broad audience, including junior to senior undergraduate students, first-year graduate students, professionals, researchers, and independent learners interested in artificial intelligence.

3. what new topics are covered in the 3rd edition?

   the third edition includes new chapters on neural networks and deep learning (including generative ai), causality, and the social, ethical, and regulatory impacts of artificial intelligence. it also features revised and updated content throughout.

4. does the book provide practical examples or code?

   yes, every concept and algorithm is illustrated with concrete examples, presented in pseudocode and open-source aipython code, enabling readers to experiment with and build upon the implementations.

5. where can i find additional resources related to the book?

   the book is supported by an online learning environment which includes code, problems, animations, lecture slides, and a knowledge representation system for experimentation. the full text of the third edition is also available online.