Decision Making Under Uncertainty: Theory and Application [Bookshelf]

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...

Decision-Making under Uncertainty and Complexity: a grounded theory approach

The topic of this paper contributes to understand the process of decision-making under uncertainty and complexity. The researcher’s main concern is to explain how decision-makers within uncertain and complex contexts make a decision. The methodology selected was Grounded Theory Methodology (GTM) which aims to develop a theory grounded in empirical data obtained in the research context.

FUZZY SOFT MATRIX THEORY AND ITS APPLICATION IN DECISION MAKING

In this work, we define fuzzy soft ($fs$) matrices and theiroperations which are more functional to make theoretical studies inthe $fs$-set theory. We then define products of $fs$-matrices andstudy their properties. We finally construct a $fs$-$max$-$min$decision making method which can be successfully applied to theproblems that contain uncertainties.

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...