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Snapshots of "best" (or "worst") experience are known to dominate human memory and may thus also have a significant effect on future behaviour. We consider here a model of repeated decision-making where, at every time step, an agent takes…

Statistical Mechanics · Physics 2022-02-18 Evangelos Mitsokapas , Rosemary J. Harris

Recovering and distinguishing between the strict-preference, indifference and/or indecisiveness parts of a decision maker's preferences is a challenging task but also important for testing theory and conducting welfare analysis. This paper…

Theoretical Economics · Economics 2025-09-15 Georgios Gerasimou

Bayesian decision theory outlines a rigorous framework for making optimal decisions based on maximizing expected utility over a model posterior. However, practitioners often do not have access to the full posterior and resort to approximate…

Machine Learning · Statistics 2019-10-29 Tomasz Kuśmierczyk , Joseph Sakaya , Arto Klami

Probabilistic classifiers are central for making informed decisions under uncertainty. Based on the maximum expected utility principle, optimal decision rules can be derived using the posterior class probabilities and misclassification…

Machine Learning · Computer Science 2025-03-25 Alexandre Perez-Lebel , Gael Varoquaux , Sanmi Koyejo , Matthieu Doutreligne , Marine Le Morvan

Recently, Halpern and Leung suggested representing uncertainty by a weighted set of probability measures, and suggested a way of making decisions based on this representation of uncertainty: maximizing weighted regret. Their paper does not…

Artificial Intelligence · Computer Science 2013-09-06 Joseph Y. Halpern

We examine behavioral axioms in decision theory that are satisfied approximately rather than exactly. We demonstrate that in key domains -- decisions under risk, uncertainty, and intertemporal choice -- behavior that \emph{almost} satisfies…

Theoretical Economics · Economics 2026-01-30 Christopher P Chambers , Federico Echenique

What is the best compromise in a situation where different people value different things? The most commonly accepted method for answering this question -- in fields across the behavioral and social sciences, decision theory, philosophy, and…

Artificial Intelligence · Computer Science 2024-10-10 Jared Moore , Yejin Choi , Sydney Levine

Theoretically as well as experimentally it is investigated how people represent their knowledge in order to make decisions or to share their knowledge with others. Experiment 1 probes into the ways how people 6ather information about the…

Artificial Intelligence · Computer Science 2013-04-15 Alf C. Zimmer

Multicriteria decision analysis aims at supporting a person facing a decision problem involving conflicting criteria. We consider an additive utility model which provides robust conclusions based on preferences elicited from the decision…

Artificial Intelligence · Computer Science 2015-02-17 K. Belahcene , C. Labreuche , N. Maudet , V. Mousseau , W. Ouerdane

Regret theory is a theory that describes human decision-making under risk. The key of obtaining a quantitative model of regret theory is to measure the preference in humans' mind when they choose among a set of options. Unlike physical…

Human-Computer Interaction · Computer Science 2018-10-02 Longsheng Jiang , Yue Wang

In this work, we present a new planning formalism called Expectation-Aware planning for decision making with humans in the loop where the human's expectations about an agent may differ from the agent's own model. We show how this…

Artificial Intelligence · Computer Science 2019-11-12 Sarath Sreedharan , Tathagata Chakraborti , Christian Muise , Subbarao Kambhampati

Emergent collective group processes and capabilities have been studied through analysis of transactive memory, measures of group task performance, and group intelligence, among others. In their approach to collective behaviors, these…

Physics and Society · Physics 2019-01-01 Yaneer Bar-Yam , David Kantor

We introduce a resource allocation framework for goal-oriented semantic networks, where participating agents assess system quality through subjective (e.g., context-dependent) perceptions. To accommodate this, our model accounts for agents…

Information Theory · Computer Science 2025-06-06 Symeon Vaidanis , Photios A. Stavrou , Marios Kountouris

A common approach to aggregate classification estimates in an ensemble of decision trees is to either use voting or to average the probabilities for each class. The latter takes uncertainty into account, but not the reliability of the…

Machine Learning · Computer Science 2022-08-17 Florian Busch , Moritz Kulessa , Eneldo Loza Mencía , Hendrik Blockeel

In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs…

Machine Learning · Computer Science 2023-02-02 Alessio Benavoli , Dario Azzimonti , Dario Piga

We live in a world brimming with uncertainty, where we constantly have to make a lot of decisions under incomplete information. We are firm believers that our subjective belief cannot be computed by rigorous mathematical formula; instead…

Physics and Society · Physics 2023-02-08 Lizhi Xin , Kevin Xin , Houwen Xin

Computer modeling of human decision making is of large importance for, e.g., sustainable transport, urban development, and online recommendation systems. In this paper we present a model for predicting the behavior of an individual during a…

Artificial Intelligence · Computer Science 2021-01-18 Chenda Zhang , Hedvig Kjellström

Despite the prevalence of voting systems in the real world there is no consensus among researchers of how people vote strategically, even in simple voting settings. This paper addresses this gap by comparing different approaches that have…

Computer Science and Game Theory · Computer Science 2019-09-24 Roy Fairstein , Adam Lauz , Kobi Gal , Reshef Meir

Egalitarian considerations play a central role in many areas of social choice theory. Applications of egalitarian principles range from ensuring everyone gets an equal share of a cake when deciding how to divide it, to guaranteeing balance…

Artificial Intelligence · Computer Science 2021-03-10 Sirin Botan , Ronald de Haan , Marija Slavkovik , Zoi Terzopoulou

This paper proposes a theoretical analysis of recommendation systems in an online setting, where items are sequentially recommended to users over time. In each round, a user, randomly picked from a population of $m$ users, requests a…

Machine Learning · Statistics 2020-10-26 Kaito Ariu , Narae Ryu , Se-Young Yun , Alexandre Proutière
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