Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence (Artificial Intelligence)

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The notions of time and change are central to the way we think about the world. Not surprisingly, both play a prominent role in artificial intelligence research, in diverse areas such as medical diagnosis, circuit debugging, naive physics, and robot planning. Reasoning About Change presents a comprehensive approach to temporal reasoning in artificial intelligence. Using techniques from temporal, nonmonotonic and epistemic logics, the author investigates issues that arise when one adopts a formal approach to temporal reasoning in artificial intelligence that is at once rigorous, efficient, and intuitive. Shoham develops a temporal logic that is based on temporal intervals rather than points in time, and presents a mathematical apparatus that simplifies and clarifies notions of nonmonotonic logic and the modal logic of knowledge. He constructs a specific logic, called Chronological Ignorance, and discusses both its practical utility and philosophical importance. In particular, he offers a new account of the concept of causation, and of its central role in commonsense reasoning. Yoav Shoham is an assistant professor in the department of Computer Science at Stanford University. Reasoning About Change is included in the Artificial Intelligence Series, edited by Michael Brady and Patrick Henry Winston.