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Understanding how subsets of items are chosen from offered sets is critical to assortment planning, wireless network planning, and many other applications. There are two seemingly unrelated subset choice models that capture dependencies…

Machine Learning · Computer Science 2023-02-23 Sander Aarts , David B. Shmoys , Alex Coy

Gambles are random variables that model possible changes in monetary wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes.…

Economics · Quantitative Finance 2016-02-03 Ole Peters , Murray Gell-Mann

The widely used Plackett-Luce ranking model assumes that individuals rank items by making repeated choices from a universe of items. But in many cases the universe is too big for people to plausibly consider all options. In the choice…

Machine Learning · Computer Science 2025-05-09 Ben Aoki-Sherwood , Catherine Bregou , David Liben-Nowell , Kiran Tomlinson , Thomas Zeng

A variety of statistical graphical models have been defined to represent the conditional independences underlying a random vector of interest. Similarly, many different graphs embedding various types of preferential independences, as for…

Artificial Intelligence · Computer Science 2016-10-26 Manuele Leonelli , Jim Q. Smith

This paper introduces a space of variable lotteries and proves a constructive version of the expected utility theorem. The word ``constructive'' is used here in two senses. First, as in constructive mathematics, the logic underlying proofs…

Theoretical Economics · Economics 2024-02-28 Kislaya Prasad

This paper considers utility indifference valuation of derivatives under model uncertainty and trading constraints, where the utility is formulated as an additive stochastic differential utility of both intertemporal consumption and…

Mathematical Finance · Quantitative Finance 2017-07-26 Huiwen Yan , Gechun Liang , Zhou Yang

We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behavior and establish conditions under which all parts of the model can be recovered from a…

General Economics · Economics 2026-02-05 Nail Kashaev , Natalia Lazzati , Ruli Xiao

In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinforcement learning problems. While utility bounds are known to…

Machine Learning · Computer Science 2011-11-14 Christos Dimitrakakis

We provide a new algorithm for solving Risk Sensitive Partially Observable Markov Decisions Processes, when the risk is modeled by a utility function, and both the state space and the space of observations is finite. This algorithm is based…

Optimization and Control · Mathematics 2022-07-19 Arsham Afsardeir , Andreas Kapetanis , Vaios Laschos , Klaus Obermayer

Auction design for the modern advertising market has gained significant prominence in the field of game theory. With the recent rise of auto-bidding tools, an increasing number of advertisers in the market are utilizing these tools for…

Computer Science and Game Theory · Computer Science 2024-12-31 Changfeng Xu , Chao Peng , Chenyang Xu , Zhengfeng Yang

This paper introduces the RUMBoost model, a novel discrete choice modelling approach that combines the interpretability and behavioural robustness of Random Utility Models (RUMs) with the generalisation and predictive ability of deep…

Machine Learning · Computer Science 2024-11-19 Nicolas Salvadé , Tim Hillel

Reliability (survival analysis, to biostatisticians) is a key ingredient for mak- ing decisions that mitigate the risk of failure. The other key ingredient is utility. A decision theoretic framework harnesses the two, but to invoke this…

Methodology · Statistics 2009-07-24 Nozer D. Singpurwalla

We develop a tractable model of realization utility that studies the role of reference-dependent S-shaped preferences in a dynamic investment setting with reinvestment. Our model generates both voluntarily realized gains and losses. It…

General Finance · Quantitative Finance 2014-08-14 Jonathan E. Ingersoll , Lawrence J. Jin

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

The problem of designing a profit-maximizing, Bayesian incentive compatible and individually rational mechanism with flexible consumers and costly heterogeneous supply is considered. In our setup, each consumer is associated with a…

Computer Science and Game Theory · Computer Science 2018-02-01 Shiva Navabi , Ashutosh Nayyar

We propose a novel definition of model exploitation in reinforcement learning. Informally, a world model is exploitable if it implies that one policy should be strictly preferred over another while the environment's true transition model…

Artificial Intelligence · Computer Science 2026-05-19 Logan Mondal Bhamidipaty , Esmeralda S. Whitammer , David Abel , Mykel J. Kochenderfer , Subramanian Ramamoorthy

We investigate the application of classification techniques to utility elicitation. In a decision problem, two sets of parameters must generally be elicited: the probabilities and the utilities. While the prior and conditional probabilities…

Artificial Intelligence · Computer Science 2013-02-01 Urszula Chajewska , Lise Getoor , Joseph Norman , Yuval Shahar

The consideration of nonstandard models of the real numbers and the definition of a qualitative ordering on those models provides a generalization of the principle of maximization of expected utility. It enables the decider to assign…

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

The standard way to evaluate language models on subjective tasks is through pairwise comparisons: an annotator chooses the "better" of two responses to a prompt. Leaderboards aggregate these comparisons into a single Bradley-Terry (BT)…

Machine Learning · Computer Science 2026-02-26 Hadi Khalaf , Serena L. Wang , Daniel Halpern , Itai Shapira , Flavio du Pin Calmon , Ariel D. Procaccia

We consider a sequence of repeated interactions between an agent and an environment. Uncertainty about the environment is captured by a probability distribution over a space of hypotheses, which includes all computable functions. Given a…

Artificial Intelligence · Computer Science 2009-12-02 Peter de Blanc
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