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Individual choices are either based on personal experience or on information provided by peers. The latter case, causes individuals to conform to the majority in their neighborhood. Such herding behavior may be very efficient in aggregating…

Physics and Society · Physics 2009-11-11 Philippe Curty , Matteo Marsili

The emergent behavior of a distributed system is conditioned by the information available to the local decision-makers. Therefore, one may expect that providing decision-makers with more information will improve system performance; in this…

Computer Science and Game Theory · Computer Science 2023-06-23 Bryce L. Ferguson , Dario Paccagnan , Jason R. Marden

We study the problem of designing mechanisms for \emph{information acquisition} scenarios. This setting models strategic interactions between an uniformed \emph{receiver} and a set of informed \emph{senders}. In our model the senders…

Computer Science and Game Theory · Computer Science 2023-06-13 Federico Cacciamani , Matteo Castiglioni , Nicola Gatti

Public support and political mobilization are two crucial factors for the adoption of ambitious climate policies in line with the international greenhouse gas reduction targets of the Paris Agreement. Despite their compound importance, they…

General Economics · Economics 2023-06-21 Simon Montfort

This work investigates a dynamic variant of Bayesian persuasion, in which a strategic sender seeks to influence a receiver's belief over time through controlling the timing of the information disclosure, under resource constraints. We…

Information Theory · Computer Science 2025-12-05 Ahmet Bugra Gundogan , Melih Bastopcu

A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an ``optimal'' predicted outcome distribution according to some…

Econometrics · Economics 2025-05-29 Anders Bredahl Kock , David Preinerstorfer

We study a problem of optimal information gathering from multiple data providers that need to be incentivized to provide accurate information. This problem arises in many real world applications that rely on crowdsourced data sets, but…

Computer Science and Game Theory · Computer Science 2017-11-27 Goran Radanovic , Adish Singla , Andreas Krause , Boi Faltings

We analyze the optimal strategy for a government to promote large-scale investment projects under information frictions. Specifically, we propose a model where the government collects information on probability of each investment and…

Theoretical Economics · Economics 2021-05-21 Keeyoung Rhee , Myungkyu Shim , Ji Zhang

Scoring rules for eliciting expert predictions of random variables are usually developed assuming that experts derive utility only from the quality of their predictions (e.g., score awarded by the rule, or payoff in a prediction market). We…

Computer Science and Game Theory · Computer Science 2011-06-14 Craig Boutilier

To take advantage of strategy commitment, a useful tactic of playing games, a leader must learn enough information about the follower's payoff function. However, this leaves the follower a chance to provide fake information and influence…

Computer Science and Game Theory · Computer Science 2023-06-14 Yurong Chen , Xiaotie Deng , Yuhao Li

This paper proposes a novel method for demand forecasting in a pricing context. Here, modeling the causal relationship between price as an input variable to demand is crucial because retailers aim to set prices in a (profit) optimal manner…

A principal hires an agent to acquire soft information about an unknown state. Even though neither how the agent learns nor what the agent discovers are contractible, we show the principal is unconstrained as to what information the agent…

Theoretical Economics · Economics 2023-07-31 Mark Whitmeyer , Kun Zhang

Autonomous cyber-physical agents and systems play an increasingly large role in our lives. To ensure that agents behave in ways aligned with the values of the societies in which they operate, we must develop techniques that allow these…

Data-based decisionmaking must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data becomes less…

Theoretical Economics · Economics 2022-12-29 Alex Frankel , Navin Kartik

Adaptive behavior in volatile environments requires agents to switch among value-control regimes across latent contexts, but maintaining separate preferences, policy biases, and action-confidence parameters for every situation is…

Machine Learning · Computer Science 2025-12-16 Jacob Poschl

Autonomous robots for gathering information on objects of interest has numerous real-world applications because of they improve efficiency, performance and safety. Realizing autonomy demands online planning algorithms to solve sequential…

Robotics · Computer Science 2024-05-07 Joshua Chesser , Thuraiappah Sathyan , Damith C. Ranasinghe

We study the design of information acquisition games-environments where a designer contracts their action on Sender's choice of experiment and the realized signals about some state-and identify which predictions can be made absent knowledge…

Theoretical Economics · Economics 2026-01-22 Eric Gao , Daniel Luo

Many smart grid frameworks, such as demand response programs, require accurate information about consumers' parameters (e.g., flexibility) at the aggregator side to optimize grid operations. Existing works typically rely on perfect…

Computer Science and Game Theory · Computer Science 2026-03-05 Hassan Mohamad , Chao Zhang , Samson Lasaulce , Olivier Beaude , Vineeth Satheeskumar Varma , Mounir Ghogho , Vincent Poor

A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by transmitting a control packet in it. Since probing all…

Data Structures and Algorithms · Computer Science 2008-04-11 Sudipto Guha , Kamesh Munagala , Saswati Sarkar

This paper studies the evaluation of policies that recommend an ordered set of items (e.g., a ranking) based on some context---a common scenario in web search, ads, and recommendation. We build on techniques from combinatorial bandits to…

Machine Learning · Computer Science 2017-11-08 Adith Swaminathan , Akshay Krishnamurthy , Alekh Agarwal , Miroslav Dudík , John Langford , Damien Jose , Imed Zitouni
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