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Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved decision-making when reducing uncertainty in specific inputs. By…

In this paper, we propose a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Given a finite collection of observations of the uncertain parameters and potential explanatory…

Optimization and Control · Mathematics 2021-09-20 Miguel Angel Muñoz , Salvador Pineda , Juan Miguel Morales

This essay looks at decision-making with interval-valued probability measures. Existing decision methods have either supplemented expected utility methods with additional criteria of optimality, or have attempted to supplement the…

Artificial Intelligence · Computer Science 2013-04-15 Ronald P. Loui

Decision-makers abhor uncertainty, and it is certainly true that the less there is of it the better. However, recognizing that uncertainty is part of the equation, particularly for deciding on environmental policy, is a prerequisite for…

Methodology · Statistics 2022-09-28 Noel Cressie

An agent acquires a costly flexible signal before making a decision. We explore to what degree knowledge of the agent's information costs helps predict her behavior. We establish an impossibility result: learning costs alone generate no…

Theoretical Economics · Economics 2023-04-05 Elliot Lipnowski , Doron Ravid

For three natural classes of dynamic decision problems; 1. additively separable problems, 2. discounted problems, and 3. discounted problems for a fixed discount factor; we provide necessary and sufficient conditions for one sequential…

Theoretical Economics · Economics 2024-05-24 Mark Whitmeyer , Cole Williams

We introduce an information order on experiments based on weighted garbling, a generalization of the standard notion of garbling. In this order, an experiment is more informative than another if the latter is a weighted garbling of the…

Theoretical Economics · Economics 2026-03-12 Daehyun Kim , Ichiro Obara

Model selection in clustering requires (i) to specify a suitable clustering principle and (ii) to control the model order complexity by choosing an appropriate number of clusters depending on the noise level in the data. We advocate an…

Information Theory · Computer Science 2010-06-03 Joachim M. Buhmann

This paper develops a category-theoretic approach to uncertainty, informativeness and decision-making problems. It is based on appropriate first order fuzzy logic in which not only logical connectives but also quantifiers have fuzzy…

General Mathematics · Mathematics 2007-05-23 P. V. Golubtsov , S. S. Moskaliuk

The quality of consequences in a decision making problem under (severe) uncertainty must often be compared among different targets (goals, objectives) simultaneously. In addition, the evaluations of a consequence's performance under the…

Artificial Intelligence · Computer Science 2022-12-15 Christoph Jansen , Georg Schollmeyer , Thomas Augustin

A decision maker's utility depends on her action $a\in A \subset \mathbb{R}^d$ and the payoff relevant state of the world $\theta\in \Theta$. One can define the value of acquiring new information as the difference between the maximum…

Theoretical Economics · Economics 2021-05-04 Farzad Pourbabaee

One purpose -- quite a few thinkers would say the main purpose -- of seeking knowledge about the world is to enhance our ability to make good decisions. An item of knowledge that can make no conceivable difference with regard to anything we…

Artificial Intelligence · Computer Science 2013-04-12 Henry E. Kyburg

In this work we generalize standard Decision Theory by assuming that two outcomes can also be incomparable. Two motivating scenarios show how incomparability may be helpful to represent those situations where, due to lack of information,…

Computer Science and Game Theory · Computer Science 2014-04-04 Piero A. Bonatti , Marco Faella , Luigi Sauro

Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action…

General Economics · Economics 2022-05-03 Stefan Rass , Sandra König , Stefan Schauer

We address the fundamental problem of selection under uncertainty by modeling it from the perspective of Bayesian persuasion. In our model, a decision maker with imperfect information always selects the option with the highest expected…

Computer Science and Game Theory · Computer Science 2024-10-16 Siddhartha Banerjee , Kamesh Munagala , Yiheng Shen , Kangning Wang

This paper presents a general framework about what is a decision problem. Our motivation is related to the fact that decision analysis and operational research are structured (as disciplines) around classes of methods, while instead we…

Artificial Intelligence · Computer Science 2023-01-10 Alberto Colorni , Alexis Tsoukiàs

We study a routing game in an environment with multiple heterogeneous information systems and an uncertain state that affects edge costs of a congested network. Each information system sends a noisy signal about the state to its subscribed…

Computer Science and Game Theory · Computer Science 2020-03-10 Manxi Wu , Saurabh Amin , Asuman E. Ozdaglar

We consider the problem of a decision-maker searching for information on multiple alternatives when information is learned on all alternatives simultaneously. The decision-maker has a running cost of searching for information, and has to…

Theoretical Economics · Economics 2020-04-13 T. Tony Ke , Wenpin Tang , J. Miguel Villas-Boas , Yuming Zhang

We explore the consequences of incomplete information in the stable marriage problem. When information capacity of the participants is increased, more favorable games are created and the quality of the matches are also better. The simple…

Statistical Mechanics · Physics 2009-11-07 Yi-Cheng Zhang

We introduce and analyze the problem of the compilation of decision models from a decision-theoretic perspective. The techniques described allow us to evaluate various configurations of compiled knowledge given the nature of evidential…

Artificial Intelligence · Computer Science 2013-04-08 David Heckerman , John S. Breese , Eric J. Horvitz