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Autonomous systems can substantially enhance a human's efficiency and effectiveness in complex environments. Machines, however, are often unable to observe the preferences of the humans that they serve. Despite the fact that the human's and…

Machine Learning · Statistics 2017-05-29 Agostino Capponi , Reza Ghanadan , Matt Stern

Auctions in which agents' payoffs are random variables have received increased attention in recent years. In particular, recent work in algorithmic mechanism design has produced mechanisms employing internal randomization, partly in…

Computer Science and Game Theory · Computer Science 2012-06-15 Shaddin Dughmi , Yuval Peres

We propose an agent-based opinion formation model characterised by a two-fold novelty. First, we realistically assume that each agent cannot measure the opinion of its neighbours with infinite resolution and accuracy, and hence it can only…

Social and Information Networks · Computer Science 2026-01-08 Carlos Andres Devia , Giulia Giordano

This paper axiomatizes, in a two-stage setup, a new theory for decision under risk and ambiguity. The axiomatized preference relation $\succeq$ on the space $\tilde{V}$ of random variables induces an ambiguity index $c$ on the space…

Optimization and Control · Mathematics 2026-03-24 Roger J. A. Laeven , Mitja Stadje

Estimating consumer preferences is central to many problems in economics and marketing. This paper develops a flexible framework for learning individual preferences from partial ranking information by interpreting observed rankings as…

Machine Learning · Statistics 2026-02-19 Yu-Chang Chen , Chen Chian Fuh , Shang En Tsai

In a consideration set model, an individual maximizes utility among the considered alternatives. I relate a consideration set additive random utility model to classic discrete choice and the extended additive random utility model, in which…

Econometrics · Economics 2024-05-24 Roy Allen

In the on-line Explore and Exploit literature, central to Machine Learning, a central planner is faced with a set of alternatives, each yielding some unknown reward. The planner's goal is to learn the optimal alternative as soon as…

Computer Science and Game Theory · Computer Science 2015-07-31 Gal Bahar , Rann Smorodinsky , Moshe Tennenholtz

Starting from the requirement that risk measures of financial portfolios should be based on their losses, not their gains, we define the notion of loss-based risk measure and study the properties of this class of risk measures. We…

Risk Management · Quantitative Finance 2014-03-26 Rama Cont , Romain Deguest , Xuedong He

Active inference, a corollary of the free energy principle, is a formal way of describing the behavior of certain kinds of random dynamical systems that have the appearance of sentience. In this chapter, we describe how active inference…

Machine Learning · Statistics 2021-10-11 Noor Sajid , Lancelot Da Costa , Thomas Parr , Karl Friston

Many policies allocate harms or benefits that are uncertain in nature: they produce distributions over the population in which individuals have different probabilities of incurring harm or benefit. Comparing different policies thus involves…

Computers and Society · Computer Science 2021-03-11 Hoda Heidari , Solon Barocas , Jon Kleinberg , Karen Levy

In the paper there is studied an optimal saving model in which the interest-rate risk for saving is a fuzzy number. The total utility of consumption is defined by using a concept of possibilistic expected utility. A notion of possibilistic…

Theoretical Economics · Economics 2020-04-22 Irina Georgescu , Jani Kinnunen

We derive a family of risk-sensitive reinforcement learning methods for agents, who face sequential decision-making tasks in uncertain environments. By applying a utility function to the temporal difference (TD) error, nonlinear…

Machine Learning · Computer Science 2014-10-10 Yun Shen , Michael J. Tobia , Tobias Sommer , Klaus Obermayer

Participation incentives is a well-known issue inhibiting randomized controlled trials (RCTs) in medicine, as well as a potential cause of user dissatisfaction for RCTs in online platforms. We frame this issue as a non-standard…

Computer Science and Game Theory · Computer Science 2026-01-13 Yingkai Li , Aleksandrs Slivkins

In our previous paper, "A Unified Approach to Systemic Risk Measures via Acceptance Set" (\textit{Mathematical Finance, 2018}), we have introduced a general class of systemic risk measures that allow for random allocations to individual…

Mathematical Finance · Quantitative Finance 2019-04-26 Francesca Biagini , Jean-Pierre Fouque , Marco Frittelli , Thilo Meyer-Brandis

In statistical practice, whether a Bayesian or frequentist approach is used in inference depends not only on the availability of prior information but also on the attitude taken toward partial prior information, with frequentists tending to…

Statistics Theory · Mathematics 2012-05-02 David R. Bickel

The expectation is an example of a descriptive statistic that is monotone with respect to stochastic dominance, and additive for sums of independent random variables. We provide a complete characterization of such statistics, and explore a…

Theoretical Economics · Economics 2024-08-06 Xiaosheng Mu , Luciano Pomatto , Philipp Strack , Omer Tamuz

We present a new approach to goal recognition that involves comparing observed facts with their expected probabilities. These probabilities depend on a specified goal g and initial state s0. Our method maps these probabilities and observed…

Artificial Intelligence · Computer Science 2024-08-27 Nils Wilken , Lea Cohausz , Christian Bartelt , Heiner Stuckenschmidt

Agent-based models are versatile tools for studying how societal opinion change, including political polarization and cultural diffusion, emerges from individual behavior. This study expands agents' psychological realism using…

Multiagent Systems · Computer Science 2017-02-22 Peter Duggins

Participatory Budgeting (PB) is commonly studied from an axiomatic perspective, where the aim is to design procedurally fair and economically efficient rules for voters with full information regarding their preferences. In contrast, we take…

Computer Science and Game Theory · Computer Science 2026-01-28 Qishen Han , Artem Ivaniuk , Edith Elkind , Lirong Xia

Opinion dynamics models such as the bounded confidence models (BCMs) describe how a population can reach consensus, fragmentation, or polarization, depending on a few parameters. Connecting such models to real-world data could help…

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