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In many sequential decision problems, an agent performs a repeated task. He then suffers regret and obtains information that he may use in the following rounds. However, sometimes the agent may also obtain information and avoid suffering…

Machine Learning · Computer Science 2025-02-25 Itai Shufaro , Nadav Merlis , Nir Weinberger , Shie Mannor

Many problems can be solved in two ways: either by adapting an existing solution, or by exchanging it for a new one. To investigate under what conditions people consider new solutions, we traced their information acquisition processes in a…

Human-Computer Interaction · Computer Science 2024-01-02 Romy Müller , Maria Pohl

What are the value and form of optimal persuasion when information can be generated only slowly? We study this question in a dynamic model in which a 'sender' provides public information over time subject to a graduality constraint, and a…

Theoretical Economics · Economics 2023-04-19 Matteo Escudé , Ludvig Sinander

It is common to evaluate a set of items by soliciting people to rate them. For example, universities ask students to rate the teaching quality of their instructors, and conference organizers ask authors of submissions to evaluate the…

Machine Learning · Statistics 2020-12-02 Jingyan Wang , Ivan Stelmakh , Yuting Wei , Nihar B. Shah

Undesired bias afflicts both human and algorithmic decision making, and may be especially prevalent when information processing trade-offs incentivize the use of heuristics. One primary example is \textit{statistical discrimination} --…

We investigate investors voluntary disclosure decisions under uncertainty about their information endowment (Dye 1985). In our model, an investor may receive initial evidence about a target firm. Conditional on learning the initial…

General Economics · Economics 2025-11-17 Jinzhi Lu , Pingyang Gao

We develop an overlapping generations model where each agent observes a verifiable private signal about the state and, with positive probability, also receives signals disclosed by his predecessor. The agent then takes an action and decides…

Theoretical Economics · Economics 2026-02-26 Nemanja Antic , Harry Pei

As artificial intelligence and machine learning tools become more accessible, and scientists face new obstacles to data collection (e.g. rising costs, declining survey response rates), researchers increasingly use predictions from…

Methodology · Statistics 2024-02-06 Kentaro Hoffman , Stephen Salerno , Awan Afiaz , Jeffrey T. Leek , Tyler H. McCormick

Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing…

Neurons and Cognition · Quantitative Biology 2015-10-01 Alan Veliz-Cuba , Zachary P. Kilpatrick , Kresimir Josic

The host of a game presents two indistinguishable envelopes to an agent. One of the envelopes is randomly selected and allocated to the agent. The agent is informed that the monetary content of one of the envelopes is twice that of the…

Other Statistics · Statistics 2015-06-16 Jeffrey Brian Tyler

The study of disparities in the liver transplantation process may focus on quantifying causal effects, particularly the average, direct, or indirect effects of various social determinants of health on being listed as a candidate for…

Language is not only used to transmit neutral information; we often seek to persuade by arguing in favor of a particular view. Persuasion raises a number of challenges for classical accounts of belief updating, as information cannot be…

Computation and Language · Computer Science 2022-09-15 Samuel A. Barnett , Thomas L. Griffiths , Robert D. Hawkins

We study a dynamic model of Bayesian persuasion in sequential decision-making settings. An informed principal observes an external parameter of the world and advises an uninformed agent about actions to take over time. The agent takes…

Computer Science and Game Theory · Computer Science 2022-05-25 Jiarui Gan , Rupak Majumdar , Goran Radanovic , Adish Singla

Motivated reasoning posits that people distort how they process information in the direction of beliefs they find attractive. This paper creates a novel experimental design to identify motivated reasoning from Bayesian updating when people…

General Economics · Economics 2022-05-26 Michael Thaler

A principal and an agent can launch a project under unanimous consent. Their individual payoffs from the project depend on an underlying state, and the agent privately knows his own preference. The principal can conduct a test to learn…

Theoretical Economics · Economics 2026-02-06 Yingkai Li , Boli Xu

In this work we generalize standard Decision Theory by assuming that two outcomes can also be incomparable. Two motivating scenarios show how incomparability may be helpful to represent those situations where, due to lack of information,…

Computer Science and Game Theory · Computer Science 2014-04-04 Piero A. Bonatti , Marco Faella , Luigi Sauro

Prediction models can improve efficiency by automating decisions such as the approval of loan applications. However, they may inherit bias against protected groups from the data they are trained on. This paper adds counterfactual…

Machine Learning · Computer Science 2024-05-03 Nicholas Tenev

Many biological, psychological and economic experiments have been designed where an organism or individual must choose between two options that have the same expected reward but differ in the variance of reward received. In this way,…

Quantitative Methods · Quantitative Biology 2018-09-20 Jared M. Field , Michael B. Bonsall

Our goal is for agents to optimize the right reward function, despite how difficult it is for us to specify what that is. Inverse Reinforcement Learning (IRL) enables us to infer reward functions from demonstrations, but it usually assumes…

Machine Learning · Computer Science 2019-06-25 Rohin Shah , Noah Gundotra , Pieter Abbeel , Anca D. Dragan

Critical decisions in hiring, college admissions, and credit lending are guided by predictions made in the presence of uncertainty. While uncertainty imparts errors across all demographic groups, this paper shows that the types of errors…

Machine Learning · Statistics 2024-10-22 Claire Lazar Reich