Integrated Offline and Online Decision Making under Uncertainty

Decision making under uncertainty

Decision making under uncertainty

1 Laboratory of Computational Neuroscience, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 2 Laboratoire de Recherché en Neuroimagerie, Le Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland 3 Information Processing and Economic Decision Making, Department of Psychology, Universität Konstanz, Konstanz, Germany 4 Economic Psychology, Department of Psychology, Univers...

An integrated approach to dynamic decision making under uncertainty

Decision making is often complicated by the dynamic and uncertain information involved. This work unifies and generalizes the major approaches to modeling and solving a subclass of such decision problems. The relevant problem characteristics include discrete problem parameters, separable optimality functions, and sequential decisions made in stages. The relevant approaches include semi-Markov d...

Decision Making under Extreme Uncertainty

Beliefs about an unknown distribution can be defined as a measure on the space of probability density functions. This paper (1) characterizes the set of beliefs that satisfy invariance postulates (2) establishes that updating invariant beliefs leads to a posterior distribution with tail asymptotically approaching 1 x(lnx)n . Note to seminar participant at Wharton: Part I of this paper is primar...

Decision Making under Interval Uncertainty

To make a decision, we must find out the user’s preference, and help the user select an alternative which is the best – according to these preferences. Traditional decision theory is based on a simplifying assumption that for each two alternatives, a user can always meaningfully decide which of them is preferable. In reality, often, when the alternatives are close, the user is often unable to s...