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We pursue an inverse approach to utility theory and consumption & investment problems. Instead of specifying an agent's utility function and deriving her actions, we assume we observe her actions (i.e. her consumption and investment…

Portfolio Management · Quantitative Finance 2015-03-17 Alexander M. G. Cox , David Hobson , Jan Obloj

This article presents a pragmatic framework for making formal, utility-based decisions from statistical inferences. The method calculates an expected utility score for an intervention by combining Bayesian posterior probabilities of…

Methodology · Statistics 2025-11-11 Will G. Hopkins

Public debates surrounding infrastructure and energy projects involve complex networks of stakeholders, arguments, and evolving narratives. Understanding these dynamics is crucial for anticipating controversies and informing engagement…

Computation and Language · Computer Science 2025-12-22 Mohamed Chenene , Jeanne Rouhier , Jean Daniélou , Mihir Sarkar , Elena Cabrio

The problem of quantification of emotions in the choice between alternatives is considered. The alternatives are evaluated in a dual manner. From one side, they are characterized by rational features defining the utility of each…

Artificial Intelligence · Computer Science 2022-03-07 V. I. Yukalov

An extension of the Hawkes model where the productivity is variable is considered. In particular, the case is considered where each point may have its own productivity and a simple analytic formula is derived for the maximum likelihood…

Applications · Statistics 2020-03-20 Frederic Paik Schoenberg

The area of declarative data analytics explores the application of the declarative paradigm on data science and machine learning. It proposes declarative languages for expressing data analysis tasks and develops systems which optimize…

Databases · Computer Science 2019-02-05 Nantia Makrynioti , Vasilis Vassalos

Local Process Models (LPM) describe structured fragments of process behavior occurring in the context of less structured business processes. Traditional LPM discovery aims to generate a collection of process models that describe highly…

Databases · Computer Science 2018-06-19 Niek Tax , Benjamin Dalmas , Natalia Sidorova , Wil M P van der Aalst , Sylvie Norre

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

Traditional learning approaches for classification implicitly assume that each mistake has the same cost. In many real-world problems though, the utility of a decision depends on the underlying context $x$ and decision $y$. However,…

Machine Learning · Computer Science 2021-04-20 Kush Bhatia , Peter L. Bartlett , Anca D. Dragan , Jacob Steinhardt

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

Participatory budgeting (PB) is a voting paradigm for distributing a divisible resource, usually called a budget, among a set of projects by aggregating the preferences of individuals over these projects. It is implemented quite extensively…

Computer Science and Game Theory · Computer Science 2024-10-29 Gogulapati Sreedurga

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to {their} expected or desirable outcomes. Deviant executions of a business…

Artificial Intelligence · Computer Science 2021-11-25 Giacomo Bergami , Chiara Di Francescomarino , Chiara Ghidini , Fabrizio Maria Maggi , Joonas Puura

Conventional automated decision-support systems often prioritize predictive accuracy, overlooking the complexities of real-world settings where stakeholders' preferences may diverge or conflict. This can lead to outcomes that disadvantage…

Machine Learning · Computer Science 2025-11-25 Vittoria Vineis , Giuseppe Perelli , Gabriele Tolomei

The predictions from an accurate prognostic model can be of great interest to patients and clinicians. When predictions are reported to individuals, they may decide to take action to improve their health or they may simply be comforted by…

Quantitative Methods · Quantitative Biology 2019-09-10 Michael C Sachs , Arvid Sjölander , Erin E Gabriel

Semivalue-based data valuation uses cooperative-game theory intuitions to assign each data point a value reflecting its contribution to a downstream task. Still, those values depend on the practitioner's choice of utility, raising the…

Artificial Intelligence · Computer Science 2026-03-11 Mélissa Tamine , Benjamin Heymann , Maxime Vono , Patrick Loiseau

We demonstrate a limitation of discounted expected utility, a standard approach for representing the preference to risk when future cost is discounted. Specifically, we provide an example of the preference of a decision maker that appears…

Computer Science and Game Theory · Computer Science 2012-02-20 Takayuki Osogami

Consider a decision maker who is responsible to collect observations so as to enhance his information in a speedy manner about an underlying phenomena of interest. The policies under which the decision maker selects sensing actions can be…

Information Theory · Computer Science 2015-06-12 Mohammad Naghshvar , Tara Javidi

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

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

We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called…

Theoretical Economics · Economics 2024-01-23 Joseph Y. Halpern , Evan Piermont