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Economists often estimate economic models on data and use the point estimates as a stand-in for the truth when studying the model's implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision…

Econometrics · Economics 2021-10-07 Maximilian Blesch , Philipp Eisenhauer

This position paper reflects on the state-of-the-art in decision-making under uncertainty. A classical assumption is that probabilities can sufficiently capture all uncertainty in a system. In this paper, the focus is on the uncertainty…

Artificial Intelligence · Computer Science 2023-03-13 Thom Badings , Thiago D. Simão , Marnix Suilen , Nils Jansen

Approaches to decision-making under uncertainty in the belief function framework are reviewed. Most methods are shown to blend criteria for decision under ignorance with the maximum expected utility principle of Bayesian decision theory. A…

Artificial Intelligence · Computer Science 2019-12-13 Thierry Denoeux

Most traditional models of uncertainty have focused on the associational relationship among variables as captured by conditional dependence. In order to successfully manage intelligent systems for decision making, however, we must be able…

Artificial Intelligence · Computer Science 2015-05-19 David Heckerman , Ross D. Shachter

Our preferences depend on the circumstances in which we reveal them. We will introduce a dependency which allows us to illustrate the relation between the possibility of winning of particular candidates in a quantum election and the type of…

Quantum Physics · Physics 2015-05-27 Marcin Makowski , Edward W. Piotrowski

We propose and axiomatize a new model of incomplete preferences under uncertainty, which we call \textit{hope-and-prepare preferences}. An act is considered more desirable than an other act when, and only when, both an optimistic…

Theoretical Economics · Economics 2025-07-29 Pierre Bardier , Bach Dong-Xuan , Van-Quy Nguyen

Decision-making under uncertainty and causal thinking are fundamental aspects of intelligent reasoning. Decision-making has been well studied when the available information is considered at the associative (probabilistic) level. The…

Artificial Intelligence · Computer Science 2026-04-30 Mauricio Gonzalez Soto , David Danks , Hugo J. Escalante Balderas , L. Enrique Sucar

Utility preference robust optimization (PRO) has recently been proposed to deal with optimal decision making problems where the decision maker's (DM) preference over gains and losses is ambiguous. In this paper, we take a step further to…

Optimization and Control · Mathematics 2024-03-11 Jian Hu , Dali Zhang , Huifu Xu , Sainan Zhang

Classical Decision Theory provides a normative framework for representing and reasoning about complex preferences. Straightforward application of this theory to automate decision making is difficult due to high elicitation cost. In response…

Artificial Intelligence · Computer Science 2013-01-30 Vu A. Ha , Peter Haddawy

In the theory of social choice the research is focused around the projection of individual preference orders to the social preference order. Also, the justification of the preference order formalism begins with the concept of utility i.e.…

Computer Science and Game Theory · Computer Science 2010-10-27 Redjan F. Shabani

The efficacy of robust optimization spans a variety of settings with uncertainties bounded in predetermined sets. In many applications, uncertainties are affected by decisions and cannot be modeled with current frameworks. This paper takes…

Optimization and Control · Mathematics 2018-03-29 Omid Nohadani , Kartikey Sharma

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk…

Theoretical Economics · Economics 2020-08-11 Christian Tarsney

We discuss conditionalisation for Accept-Desirability models in an abstract decision-making framework, where uncertain rewards live in a general linear space, and events are special projection operators on that linear space. This abstract…

Artificial Intelligence · Computer Science 2025-12-23 Kathelijne Coussement , Gert de Cooman , Keano De Vos

We consider a model where an agent is must choose between alternatives that each provide only an imprecise description of the world (e.g. linguistic expressions). The set of alternatives is closed under logical conjunction and disjunction,…

Theoretical Economics · Economics 2024-09-11 Evan Piermont , Marcus Pivato

Nontransitive choices have long been an area of curiosity within economics. However, determining whether nontransitive choices represent an individual's preference is a difficult task since choice data is inherently stochastic. This paper…

Theoretical Economics · Economics 2023-05-01 Mogens Fosgerau , John Rehbeck

The reasoning with qualitative uncertainty measures involves comparative statements about events in terms of their likeliness without necessarily assigning an exact numerical value to these events. The paper is divided into two parts. In…

Logic · Mathematics 2024-03-18 Marta Bilkova , Sabine Frittella , Daniil Kozhemiachenko , Ondrej Majer

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main…

Multiagent Systems · Computer Science 2020-11-06 Kshitij Kulkarni , Sven Neth

We study a simple example of a sequential game illustrating problems connected with making rational decisions that are universal for social sciences. The set of chooser's optimal decisions that manifest his preferences in case of a constant…

Physics and Society · Physics 2007-05-23 Edward W. Piotrowski , Marcin Makowski

Preferences among acts are analyzed in the style of L. Savage, but as partially ordered. The rationality postulates considered are weaker than Savage's on three counts. The Sure Thing Principle is derived in this setting. The postulates are…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

We provide a decision-theoretic framework for dealing with uncertainty in quantum mechanics. This uncertainty is two-fold: on the one hand there may be uncertainty about the state the quantum system is in, and on the other hand, as is…

Quantum Physics · Physics 2026-05-01 Keano De Vos , Gert de Cooman , Alexander Erreygers , Jasper De Bock