Operations’ decision making under uncertainty: case studies on papermaking

Decision Making under Uncertainty: Operations Research Meets AI (Again)

Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have been studied in operations research for decades. The recent incorporation of ideas from many areas of AI, including planning, probabilistic modeling, machine learning, and knowledge representation) have made these models much more widely applicable. I briefly survey recent advances within AI i...

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...

Cognitive Constraints on Decision Making under Uncertainty

IntroductIon Models of decision making under uncertainty should be grounded in general cognitive processes reflecting pervasive constraints from the nature of our environment. Developing integrated models applicable across different tasks provides converging constraints that increase the predictiveness of models to new situations. Decision making is such a rich discipline that it is often consi...

Reflections on Decision Making under Uncertainty