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Recent decades have witnessed developments in decision theory that propose an alternative to the accepted Bayesian view. According to this view, all uncertainty can be quantified by probability measures. This view has been criticized on empirical as well as conceptual grounds. David Schmeidler has offered an alternative way of thinking about decision under uncertainty, which has become popular in recent years.
This book provides a review and an introduction to this new decision theory under uncertainty. The first part focuses on theory axiomatizations, the definition of uncertainty aversion, the issue of updating and independence, and so forth. The second part deals with applications to economic theory, game theory and finance. With a wide variety of contributions of the highest order, the book can be considered to be extremely authoritative.
This is the first collection to include papers on this topic, and it can thus serve as an introduction to researchers who are new to the field or a graduate textbook. With this goal in mind, the book contains survey introductions that are aimed at a graduate level student, and help explain the main ideas, as well as put them in perspective.