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Related papers: Evaluating gambles using dynamics

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Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To…

Ergodicity economics is a new branch of economic theory that notes the conceptual difference between time averages and expectation values, which coincide only for ergodic observables. It postulates that individual agents maximise the time…

Economics · Quantitative Finance 2021-03-02 Ole Peters , Alexander Adamou

We show in a simulation when economic agents are subject to evolution (random change and selection based on the success in the estimation of the result of the gamble) they acquire risk aversive behavior. This behavior appears in the form of…

Physics and Society · Physics 2024-02-07 Ihor Kendiukhov

We introduce capital games, which generalize the definition of standard games to incorporate dynamics. In capital games, payoffs are in units of capital which are not assumed to be units of utility. The dynamics allow us to infer player…

Computer Science and Game Theory · Computer Science 2026-01-27 Ben Abramowitz

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 typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

The desirable gambles framework provides a foundational approach to imprecise probability theory but relies heavily on linear utility assumptions. This paper introduces function-coherent gambles, a generalization that accommodates…

Theoretical Economics · Economics 2025-04-28 Gregory Wheeler

Gambits are central to human decision-making. Our goal is to provide a theory of Gambits. A Gambit is a combination of psychological and technical factors designed to disrupt predictable play. Chess provides an environment to study gambits…

Theoretical Economics · Economics 2022-04-14 Shiva Maharaj , Nicholas Polson , Christian Turk

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

Sequences of repeated gambles provide an experimental tool to characterize the risk preferences of humans or artificial decision-making agents. The difficulty of this inference depends on factors including the details of the gambles offered…

Artificial Intelligence · Computer Science 2023-08-15 James Price , Colm Connaughton

In the large financial market, which is described by a model with countably many traded assets, we formulate the problem of the expected utility maximization. Assuming that the preferences of an economic agent are modeled with a stochastic…

Portfolio Management · Quantitative Finance 2014-10-21 Oleksii Mostovyi

We obtain an elementary characterization of expected utility based on a representation of choice in terms of psychological gambles, which requires no assumption other than coherence between ex-ante and ex-post preferences. Weaker version of…

General Economics · Economics 2024-11-05 Gianluca Cassese

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

Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat other domain attributes: as a random variable with a density…

Artificial Intelligence · Computer Science 2013-01-18 Urszula Chajewska , Daphne Koller

We consider the robust exponential utility maximization problem in discrete time: An investor maximizes the worst case expected exponential utility with respect to a family of nondominated probabilistic models of her endowment by…

Portfolio Management · Quantitative Finance 2019-02-12 Daniel Bartl

The desirable gambles framework provides a rigorous foundation for imprecise probability theory but relies heavily on linear utility via its coherence axioms. In our related work, we introduced function-coherent gambles to accommodate…

Theoretical Economics · Economics 2025-03-06 Gregory Wheeler

We study a dynamic game where an expert sends probabilistic forecasts to a decision-maker. The decision-maker verifies these forecasts using a calibration test based on past data. How should the expert send forecasts to maximize her payoff…

Theoretical Economics · Economics 2026-05-13 Atulya Jain , Vianney Perchet

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

We construct a model of an exchange economy in which agents trade assets contingent on an observable signal, the probability of which depends on public opinion. The agents in our model are replaced occasionally and each person updates…

Theoretical Economics · Economics 2022-04-28 Jean-Philippe Bouchaud , Roger Farmer

I show that if the capital accumulation dynamics is stochastic a new term, in addition to that given by accounting prices, has to be introduced in order to derive a correct estimate of the genuine wealth of an economy. In a simple model…

General Finance · Quantitative Finance 2008-12-02 M. Marsili

This paper studies a new and more general axiomatization than one presented previously for preference on likelihood gambles. Likelihood gambles describe actions in a situation where a decision maker knows multiple probabilistic models and a…

Artificial Intelligence · Computer Science 2012-07-02 Phan H. Giang
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