Reasoning about Uncertainty

Uncertainty is a fundamental and unavoidable feature of daily life; in order to dealwith uncertaintly intelligently, we need to be able to represent it and reason about it. In thisbook, Joseph Halpern examines formal ways of representing uncertainty and considers various logicsfor reasoning about it. While the ideas presented are formalized in terms of definitions andtheorems, the emphasis is on the philosophy of representing and reasoning about uncertainty; thematerial is accessible and relevant to researchers and students in many fields, including computerscience, artificial intelligence, economics (particularly game theory), mathematics, philosophy, andstatistics.Halpern begins by surveying possible formal systems for representing uncertainty,including probability measures, possibility measures, and plausibility measures. He considers theupdating of beliefs based on changing information and the relation to Bayes' theorem; this leads toa discussion of qualitative, quantitative, and plausibilistic Bayesian networks. He considers notonly the uncertainty of a single agent but also uncertainty in a multi-agent framework. Halpern thenconsiders the formal logical systems for reasoning about uncertainty. He discusses knowledge andbelief; default reasoning and the semantics of default; reasoning about counterfactuals, andcombining probability and counterfactuals; belief revision; first-order modal logic; and statisticsand beliefs. He includes a series of exercises at the end of each chapter.