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We present a model of a forecaster who must predict the future value of a variable that depends on an exogenous state and on the intervention of a policy-maker. We investigate the incentives of the forecaster to acquire costly private…

Theoretical Economics · Economics 2026-04-02 Augusto Nieto-Barthaburu

We consider a ubiquitous scenario in the Internet economy when individual decision-makers (henceforth, agents) both produce and consume information as they make strategic choices in an uncertain environment. This creates a three-way…

Computer Science and Game Theory · Computer Science 2021-04-09 Yishay Mansour , Aleksandrs Slivkins , Vasilis Syrgkanis , Zhiwei Steven Wu

We study an information acquisition problem in which an informed trader acquires costly information prior to trading in the Kyle equilibrium. The cost of information acquisition is represented by an entropy cost. Regardless of the prior…

Theoretical Economics · Economics 2026-03-24 S. Viswanathan , Hao Xing

We study how long-lived, rational agents learn in a social network. In every period, after observing the past actions of his neighbors, each agent receives a private signal, and chooses an action whose payoff depends only on the state.…

Theoretical Economics · Economics 2024-07-22 Wanying Huang , Philipp Strack , Omer Tamuz

User preference learning is generally a hard problem. Individual preferences are typically unknown even to users themselves, while the space of choices is infinite. Here we study user preference learning from information-theoretic…

Machine Learning · Computer Science 2023-11-27 Tanya Ignatenko , Kirill Kondrashov , Marco Cox , Bert de Vries

A sequential decision-making agent balances between exploring to gain new knowledge about an environment and exploiting current knowledge to maximize immediate reward. For environments studied in the traditional literature, optimal…

Machine Learning · Computer Science 2024-07-23 Dilip Arumugam , Wanqiao Xu , Benjamin Van Roy

We introduce an epistemic information measure between two data streams, that we term $influence$. Closely related to transfer entropy, the measure must be estimated by epistemic agents with finite memory resources via sampling accessible…

We propose and design recommendation systems that incentivize efficient exploration. Agents arrive sequentially, choose actions and receive rewards, drawn from fixed but unknown action-specific distributions. The recommendation system…

Computer Science and Game Theory · Computer Science 2026-04-02 Nicole Immorlica , Jieming Mao , Aleksandrs Slivkins , Zhiwei Steven Wu

Evidence-based decision-making entails collecting (costly) observations about an underlying phenomenon of interest, and subsequently committing to an (informed) decision on the basis of accumulated evidence. In this setting, active sensing…

Machine Learning · Statistics 2020-06-26 Daniel Jarrett , Mihaela van der Schaar

In the latent bandit problem, the learner has access to reward distributions and -- for the non-stationary variant -- transition models of the environment. The reward distributions are conditioned on the arm and unknown latent states. The…

Machine Learning · Computer Science 2022-07-11 Alexander Galozy , Slawomir Nowaczyk

We propose a novel adaptive design for clinical trials with time-to-event outcomes and covariates (which may consist of or include biomarkers). Our method is based on the expected entropy of the posterior distribution of a proportional…

Applications · Statistics 2016-03-29 James E. Barrett

A decision maker is choosing between an active action (e.g., purchase a house, invest certain stock) and a passive action. The payoff of the active action depends on the buyer's private type and also an unknown state of nature. An…

Computer Science and Game Theory · Computer Science 2021-10-29 Shuze Liu , Weiran Shen , Haifeng Xu

Whereas deterministic protocols are typically guaranteed to obtain particular goals of interest, probabilistic protocols typically provide only probabilistic guarantees. This paper initiates an investigation of the interdependence between…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-08 Nitzan Zamir , Yoram Moses

We explore a model of non-Bayesian information aggregation in networks. Agents non-cooperatively choose among Friedkin-Johnsen type aggregation rules to maximize payoffs. The DeGroot rule is chosen in equilibrium if and only if there is…

General Economics · Economics 2023-11-15 Abhijit Banerjee , Olivier Compte

A principal who values an object allocates it to one or more agents. Agents learn private information (signals) from an information designer about the allocation payoff to the principal. Monetary transfer is not available but the principal…

Theoretical Economics · Economics 2022-10-31 Yi-Chun Chen , Gaoji Hu , Xiangqian Yang

We study a communication game between a sender and a receiver. The sender chooses one of her signals about the state of the world (i.e., anecdotes) and communicates to the receiver who takes an action affecting both players. The sender and…

Theoretical Economics · Economics 2024-07-19 Nika Haghtalab , Nicole Immorlica , Brendan Lucier , Markus Mobius , Divyarthi Mohan

We consider the problem of distributed inference where agents in a network observe a stream of private signals generated by an unknown state, and aim to uniquely identify this state from a finite set of hypotheses. We focus on scenarios…

Systems and Control · Electrical Eng. & Systems 2021-09-01 Aritra Mitra , John A. Richards , Saurabh Bagchi , Shreyas Sundaram

Suppose we have three independent copies of a regular diffusion on $[0,1]$ with absorbing boundaries. Of these diffusions, either at least two are absorbed at the upper boundary or at least two at the lower boundary. In this way, they…

Probability · Mathematics 2011-12-30 Saul Jacka , Jon Warren , Peter Windridge

We study a data analyst's problem of acquiring data from self-interested individuals to obtain an accurate estimation of some statistic of a population, subject to an expected budget constraint. Each data holder incurs a cost, which is…

Computer Science and Game Theory · Computer Science 2019-05-15 Yiling Chen , Shuran Zheng

Experimental design is crucial for inference where limitations in the data collection procedure are present due to cost or other restrictions. Optimal experimental designs determine parameters that in some appropriate sense make the data…

Machine Learning · Statistics 2016-03-11 Panagiotis Tsilifis , Roger G. Ghanem , Paris Hajali