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Cloth hardcover, x + 179 pages, NOT ex-library. Minor handling wear. Book is clean and bright, untanned with unmarked text, free of inscriptions and stamps, firmly bound. No dust jacket. Partially removed retail barcode sticker on the back. -- The book provides a comprehensive introduction to nonmonotonic reasoning, a branch of artificial intelligence (AI) focused on reasoning systems where conclusions drawn can be withdrawn in the light of new evidence. Unlike classical logic systems, where inferences are definitive, nonmonotonic reasoning allows for more flexible and realistic approaches to decision-making in uncertain environments, reflecting the way human reasoning often functions. The book explores various systems and formal frameworks developed to handle nonmonotonic reasoning, including default logic, autoepistemic logic, and circumscription. The authors guide readers through the theory, applications, and limitations of these frameworks, making this volume a critical resource for anyone studying AI, knowledge representation, or logic programming. Topics covered in the book include: - Default logic and its role in handling incomplete information; - Circumscription and how it enables minimal model reasoning; - Autoepistemic logic, which deals with reasoning about one's own beliefs; - Logic programming with negation and how it relates to nonmonotonic reasoning; - Applications of nonmonotonic reasoning in AI systems, database theory, and expert systems; - Comparative analysis of nonmonotonic reasoning systems. This work is suitable for researchers, graduate students, and professionals in AI, offering both theoretical insights and practical examples of nonmonotonic reasoning systems.
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