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A family of models of individual discrete choice are constructed by means of statistical averaging of choices made by a subject in a reinforcement learning process, where the subject has short, k-term memory span. The choice probabilities…

Econometrics · Economics 2019-08-20 Misha Perepelitsa

This short note is devoted to the unraveling of the hidden interactivity of ordinary games which is an artefact of predictions of the behaviour of other players by the fixed player and describes deviations of their real behaviour from such…

Optimization and Control · Mathematics 2007-05-23 Denis V. Juriev

We provide sufficient conditions under which a utility function may be recovered from a finite choice experiment. Identification, as is commonly understood in decision theory, is not enough. We provide a general recoverability result that…

Theoretical Economics · Economics 2023-01-30 Christopher P. Chambers , Federico Echenique , Nicolas S. Lambert

We extend well-known comparative results under expected utility to models of non-expected utility by providing novel conditions on local utility functions. We illustrate how our results parallel, and are distinct from, existing results for…

Theoretical Economics · Economics 2026-01-16 Collin Raymond , Yangwei Song

Ramsey (1926) sketches a proposal for measuring the subjective probabilities of an agent by their observable preferences, assuming that the agent is an expected utility maximizer. I show how to extend the spirit of Ramsey's method to a…

Computer Science and Game Theory · Computer Science 2019-07-23 Sven Neth

We initiate a novel direction in randomized social choice by proposing a new definition of agent utility for randomized outcomes. Each agent has a preference over all outcomes and a {\em quantile} parameter. Given a {\em lottery} over the…

Computer Science and Game Theory · Computer Science 2026-03-03 Ioannis Caragiannis , Fabian Frank , Sanjukta Roy

One common assumption in game theory is that any player optimizes a utility function that takes into account only its own payoff. However, it has long been observed that in real life players may adopt an altruistic or even spiteful…

Computer Science and Game Theory · Computer Science 2025-11-25 Michail Fasoulakis , Leonidas Bakopoulos , Charilaos Akasiadis , Georgios Chalkiadakis

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman

Noncooperative games with uncertain payoffs have been classically studied under the expected-utility theory framework, which relies on the strong assumption that agents behave rationally. However, simple experiments on human decision makers…

Computer Science and Game Theory · Computer Science 2025-08-14 Ashok Krishnan K. S. , Hélène Le Cadre , Ana Bušić

In the present article we use the quantum formalism to describe the effects of risk and ambiguity in decision theory. The main idea is that the probabilities in the classic theory of expected utility are estimated probabilities, and thus do…

General Physics · Physics 2011-09-21 Riccardo Franco

We give elementary examples within a framework for studying decisions under uncertainty where probabilities are only roughly known. The framework, in gambling terms, is that the size of a bet is proportional to the gambler's perceived…

Probability · Mathematics 2023-12-19 David J. Aldous , F. Thomas Bruss

We provide a theoretical framework to understand how widely used measures of choice difficulty relate. In a binary-option Bayesian expected-utility framework, we show that three measures of difficulty, (i) understanding (ex-ante value),…

Theoretical Economics · Economics 2026-04-30 Chris Chambers , Yusufcan Masatolioglu , Paulo Natenzon , Collin Raymond

We elicit incomplete preferences over monetary gambles with subjective uncertainty. Subjects rank gambles, and these rankings are used to estimate preferences; payments are based on estimated preferences. About 40\% of subjects express…

General Economics · Economics 2022-10-06 Kirby Nielsen , Luca Rigotti

We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying "true" preference. Our conditions are weak, and therefore valid in a wide range of economic environments.…

Theoretical Economics · Economics 2020-11-03 Christopher P. Chambers , Federico Echenique , Nicolas Lambert

Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This…

Economics · Quantitative Finance 2016-10-07 Enrico G. De Giorgi , Ola Mahmoud

We introduce language-based games, a generalization of psychological games [6] that can also capture reference-dependent preferences [7]. The idea is to extend the domain of the utility function to situations, maximal consistent sets in…

Computer Science and Game Theory · Computer Science 2013-10-28 Adam Bjorndahl , Joseph Y. Halpern , Rafael Pass

Motivated by the analysis of a general optimal portfolio selection problem, which encompasses as special cases an optimal consumption and an optimal debt-arrangement problem, we are concerned with the questions of how a personality trait…

Theoretical Economics · Economics 2023-11-14 Francesco Ruscitti , Ram Sewak Dubey , Giorgio Laguzzi

Probabilistic risk aversion, defined through quasi-convexity in probabilistic mixtures, is a common useful property in decision analysis. We study a general class of non-monotone mappings, called the generalized rank-dependent functions,…

Theoretical Economics · Economics 2024-09-30 Ruodu Wang , Qinyu Wu

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e.…

Machine Learning · Statistics 2016-10-07 Pedro A. Ortega , Alan A. Stocker

Approaches for estimating preferences from human annotated data typically involves inducing a distribution over a ranked list of choices such as the Plackett-Luce model. Indeed, modern AI alignment tools such as Reward Modelling and Direct…

Machine Learning · Statistics 2025-08-20 Chirag Nagpal