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Belief revision is a topic of much interest in theoretical computer science and logic, and it forms a central problem in research into artificial intelligence. In simple terms: how do you update a database of knowledge in the light of new information? What if the new information is in conflict with something that was previously held to be true? An intelligent system should be able to accommodate all such cases. This book contains a collection of research articles on belief revision that are completely up to date and an introductory chapter that presents a survey of current research in the area and the fundamentals of the theory. Thus this volume will be useful as a textbook on belief revision.