Belief Revision: Fundamentals and Applications
Kuhusu kitabu pepe hiki
The process of altering one's views in order to take into account a new piece of knowledge is referred to as belief revision. Philosophy, database design, and artificial intelligence are all areas of study that are contributing to research on the logical formalization of belief revision for the construction of rational beings.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Belief revision
Chapter 2: Axiom
Chapter 3: Deductive reasoning
Chapter 4: Abductive reasoning
Chapter 5: Inductive logic programming
Chapter 6: Non-monotonic logic
Chapter 7: Description logic
Chapter 8: Dempster-Shafer theory
Chapter 9: Default logic
Chapter 10: Epistemic modal logic
(II) Answering the public top questions about belief revision.
(III) Real world examples for the usage of belief revision in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of belief revision.
What is Artificial Intelligence Series
The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
