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Evidence suggests that participants in strategy-proof matching mechanisms play dominated strategies. To explain the data, we introduce expectation-based loss aversion into a school-choice setting and characterize choice-acclimating personal…

Theoretical Economics · Economics 2024-08-28 Vincent Meisner , Jonas von Wangenheim

In biology and ecology, individuals or communities of individuals living in unpredictable environments often alternate between different evolutionary strategies to spread and reduce risks. Such behavior is commonly referred to as…

Populations and Evolution · Quantitative Biology 2015-03-11 Jorge Hidalgo , Simone Pigolotti , Miguel A. Munoz

Currently the Dempster-Shafer based algorithm and Uniform Random Probability based algorithm are the preferred method of resolving security games, in which defenders are able to identify attackers and only strategy remained ambiguous.…

Artificial Intelligence · Computer Science 2015-08-11 Hossein Khani , Mohsen Afsharchi

In observational studies of discrimination, the most common statistical approaches consider either the rate at which decisions are made (benchmark tests) or the success rate of those decisions (outcome tests). Both tests, however, have…

Applications · Statistics 2025-03-07 Johann D. Gaebler , Sharad Goel

This paper develops a theory of learning under ambiguity induced by the decision maker's beliefs about the collection of data correlated with the true state of the world. Within our framework, two classical results on Bayesian learning…

Theoretical Economics · Economics 2026-02-10 Cheaheon Lim

We study the problem of repeated two-sided matching with uncertain preferences (two-sided bandits), and no explicit communication between agents. Recent work has developed algorithms that converge to stable matchings when one side (the…

Multiagent Systems · Computer Science 2025-08-13 Gaurab Pokharel , Sanmay Das

Recent research in multi-agent reinforcement learning (MARL) has shown success in learning social behavior and cooperation. Social dilemmas between agents in mixed-sum settings have been studied extensively, but there is little research…

Artificial Intelligence · Computer Science 2023-05-01 Ram Rachum , Yonatan Nakar , Reuth Mirsky

Facing an unknown situation, a person may not be able to firmly elicit his/her preferences over different alternatives, so he/she tends to express uncertain preferences. Given a community of different persons expressing their preferences…

Artificial Intelligence · Computer Science 2017-08-11 Yiru Zhang , Tassadit Bouadi , Arnaud Martin

We use three kinds of computations: simulation, numeric, and symbolic, to guide risk-averse gamblers in general, and offer particular advice on how to resolve the famous St. Petersburg paradox.

History and Overview · Mathematics 2023-10-12 Lucy Martinez , Doron Zeilberger

This paper introduces a qualitative measure of ambiguity and analyses its relationship with other measures of uncertainty. Probability measures relative likelihoods, while ambiguity measures vagueness surrounding those judgments. Ambiguity…

Artificial Intelligence · Computer Science 2013-03-08 Michael S. K. M. Wong , Z. W. Wang

A stylized experiment, the public goods game, has taught us the peculiar reproducible fact that humans tend to contribute more to shared resources than expected from economically rational assumptions. There have been two competing…

Physics and Society · Physics 2024-12-03 Chen Shen , Zhixue He , Hao Guo , Shuyue Hu , Jun Tanimoto , Lei Shi , Petter Holme

We consider active learning under incentive compatibility constraints. The main application of our results is to economic experiments, in which a learner seeks to infer the parameters of a subject's preferences: for example their attitudes…

Computer Science and Game Theory · Computer Science 2019-11-15 Federico Echenique , Siddharth Prasad

Existing observational approaches for learning human preferences, such as inverse reinforcement learning, usually make strong assumptions about the observability of the human's environment. However, in reality, people make many important…

Machine Learning · Statistics 2021-10-29 Cassidy Laidlaw , Stuart Russell

Many real life situations require a set of items to be repeatedly placed in a random sequence. In such circumstances, it is often desirable to test whether such randomization indeed obtains, yet this problem has received very limited…

Applications · Statistics 2023-04-14 Darren Grant

We study three axioms in the model of constrained social choice under uncertainty where (i) agents have subjective expected utility preferences over acts and (ii) different states of nature have (possibly) different sets of available…

Theoretical Economics · Economics 2024-08-05 Eric Bahel

We introduce an information order on experiments based on weighted garbling, a generalization of the standard notion of garbling. In this order, an experiment is more informative than another if the latter is a weighted garbling of the…

Theoretical Economics · Economics 2026-03-12 Daehyun Kim , Ichiro Obara

We consider statistical Markov Decision Processes where the decision maker is risk averse against model ambiguity. The latter is given by an unknown parameter which influences the transition law and the cost functions. Risk aversion is…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Ulrich Rieder

Experiments on decision making under uncertainty are known to display a classical pattern of risk aversion and risk seeking referred to as "fourfold pattern" (or "reflection effect") , but recent experiments varying the speed and order of…

Neurons and Cognition · Quantitative Biology 2024-01-17 Francesco Fumarola , Lukasz Kusmierz , Ronald B. Dekker

Accurately modeling human decision-making in security is critical to thinking about when, why, and how to recommend that users adopt certain secure behaviors. In this work, we conduct behavioral economics experiments to model the…

Computer Science and Game Theory · Computer Science 2018-05-18 Elissa M. Redmiles , Michelle L. Mazurek , John P. Dickerson

Agents' learning from feedback shapes economic outcomes, and many economic decision-makers today employ learning algorithms to make consequential choices. This note shows that a widely used learning algorithm, $\varepsilon$-Greedy, exhibits…

Machine Learning · Computer Science 2023-12-13 Andreas Haupt , Aroon Narayanan