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One purpose -- quite a few thinkers would say the main purpose -- of seeking knowledge about the world is to enhance our ability to make good decisions. An item of knowledge that can make no conceivable difference with regard to anything we…

Artificial Intelligence · Computer Science 2013-04-12 Henry E. Kyburg

Social learning is a fundamental mechanism shaping decision-making across numerous social networks, including social trading platforms. In those platforms, investors combine traditional investing with copying the behavior of others.…

Physics and Society · Physics 2025-07-04 Bijin Joseph , Christoph Riedl , Alex Pentland , Esteban Moro

Excess individual creativity can be detrimental to society because creators invest in unproven ideas at the expense of propagating proven ones. Moreover, a proportion of individuals can benefit from creativity without being creative…

Computers and Society · Computer Science 2014-08-13 Liane Gabora , Simon Tseng

Although both data availability and the demand for accurate forecasts are increasing, collaboration between stakeholders is often constrained by data ownership and competitive interests. In contrast to recent proposals within cooperative…

Machine Learning · Computer Science 2026-05-14 Michael Vitali , Pierre Pinson

Prediction markets are often described as mechanisms that ``aggregate information'' into prices, yet the mapping from dispersed private information to observed market histories is typically noisy, endogenous, and shaped by heterogeneous and…

Mathematical Finance · Quantitative Finance 2026-01-28 Juan Pablo Madrigal-Cianci , Camilo Monsalve Maya , Lachlan Breakey

There are both benefits and drawbacks to cultural diversity. It can lead to friction and exacerbate differences. However, as with biological diversity, cultural diversity is valuable in times of upheaval; if a previously effective solution…

Neurons and Cognition · Quantitative Biology 2019-07-19 Liane Gabora , Stefan Leijnen

Prior beliefs are central to Bayesian accounts of cognition, but many of these accounts do not directly measure priors. More specifically, initial states of belief heavily influence how new information is assumed to be utilized when…

Neurons and Cognition · Quantitative Biology 2022-01-11 Peter A. V. DiBerardino , Alexandre L. S. Filipowicz , James Danckert , Britt Anderson

An agent acquires a costly flexible signal before making a decision. We explore to what degree knowledge of the agent's information costs helps predict her behavior. We establish an impossibility result: learning costs alone generate no…

Theoretical Economics · Economics 2023-04-05 Elliot Lipnowski , Doron Ravid

Identifying important scholarly literature at an early stage is vital to the academic research community and other stakeholders such as technology companies and government bodies. Due to the sheer amount of research published and the growth…

Digital Libraries · Computer Science 2020-12-29 Akhil Pandey Akella , Hamed Alhoori , Pavan Ravikanth Kondamudi , Cole Freeman , Haiming Zhou

Consumer behavior under social influence is a well-known phenomenon and computer scientists and economists are prevalently trying to analyze the dynamics behind decision making during the consumption process through agent-based modeling…

Social and Information Networks · Computer Science 2022-10-18 Eren Arkangil

Despite strong evidence for peer effects, little is known about how individuals balance intrinsic preferences and social learning in different choice environments. Using a combination of experiments and discrete choice modeling, we show…

General Economics · Economics 2024-02-29 Fabian Dvorak , Urs Fischbacher

Governments are increasingly turning to algorithmic risk assessments when making important decisions, such as whether to release criminal defendants before trial. Policymakers assert that providing public servants with algorithmic advice…

Human-Computer Interaction · Computer Science 2021-08-16 Ben Green , Yiling Chen

In many prediction problems, the predictive model affects the distribution of the prediction target. This phenomenon is known as performativity and is often caused by the behavior of individuals with vested interests in the outcome of the…

Machine Learning · Statistics 2024-06-03 Seamus Somerstep , Ya'acov Ritov , Yuekai Sun

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} --…

Variance in predictions across different trained models is a significant, under-explored source of error in fair binary classification. In practice, the variance on some data examples is so large that decisions can be effectively arbitrary.…

The provision of information can improve individual judgments but also fail to make group decisions more accurate; if individuals choose to attend to the same information in the same manner, the predictive diversity that enables crowd…

General Economics · Economics 2025-12-29 Jon Atwell , Marlon Twyman

Binary decision-making process is ubiquitous in social life and is of vital significance in many real-world issues, ranging from public health to political campaigns. While continuous opinion evolution independent of discrete choice…

Physics and Society · Physics 2021-05-26 Xuyang Chen , Xin Wang , Longzhao Liu , Shaoting Tang , Zhiming Zheng

In social network markets, the act of consumer choice in these industries is governed not just by the set of incentives described by conventional consumer demand theory, but by the choices of others in which an individual's payoff is an…

Social and Information Networks · Computer Science 2012-10-08 Paul Ormerod , Bassel Tarbush , R. Alexander Bentley

Social learning, copying other's behavior without actual experience, offers a cost-effective means of knowledge acquisition. However, it raises the fundamental question of which individuals have reliable information: successful individuals…

Social and Information Networks · Computer Science 2022-03-08 Anil Yaman , Nicolas Bredeche , Onur Çaylak , Joel Z. Leibo , Sang Wan Lee

In this paper, we consider one aspect of the problem of applying decision theory to the design of agents that learn how to make decisions under uncertainty. This aspect concerns how an agent can estimate probabilities for the possible…

Artificial Intelligence · Computer Science 2013-03-26 Adam J. Grove , Daphne Koller
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