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 simplest terms it addresses the problem of updating a database of knowledge in the light of new information and what to do in the case where new information is in conflict with something that was previously held to be true. The problem is central to the study of artificial intelligence, because an intelligent system should be able to accomodate all such cases. This book contains a collection of up-to-date research articles on belief revision and an introductory chapter that presents a survey of current research in the area and the fundamentals of the theory.