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Humans and animals explore their environment and acquire useful skills even in the absence of clear goals, exhibiting intrinsic motivation. The study of intrinsic motivation in artificial agents is concerned with the following question:…

Machine Learning · Computer Science 2021-12-08 Nicholas Rhinehart , Jenny Wang , Glen Berseth , John D. Co-Reyes , Danijar Hafner , Chelsea Finn , Sergey Levine

We study the problem of a principal who wants to influence an agent's observable action, subject to an ex-post budget. The agent has a private type determining their cost function. This paper endogenizes the value of the resource driving…

Theoretical Economics · Economics 2024-04-25 Nicole Immorlica , Nicholas Wu , Brendan Lucier

We design and implement lab experiments to evaluate the normative appeal of behavior arising from models of ambiguity-averse preferences. We report two main empirical findings. First, we demonstrate that behavior reflects an incomplete…

Theoretical Economics · Economics 2024-07-26 Christoph Kuzmics , Brian W. Rogers , Xiannong Zhang

Strategic learning studies how decision rules interact with agents who may strategically change their inputs/features to achieve better outcomes. In standard settings, models assume that the decision-maker's sole scope is to learn a…

Computer Science and Game Theory · Computer Science 2025-10-23 Valia Efthymiou , Ekaterina Fedorova , Chara Podimata

Correlated equilibria enable a coordinator to influence the self-interested agents by recommending actions that no player has an incentive to deviate from. However, the effectiveness of this mechanism relies on accurate knowledge of the…

Computer Science and Game Theory · Computer Science 2026-05-18 Jaehan Im , Ufuk Topcu , David Fridovich-Keil

We study optimal dynamic persuasion in a bandit experimentation model where a principal, unlike in standard settings, has a single-peaked preference over the agent's stopping time. This non-monotonic preference arises because maximizing the…

Theoretical Economics · Economics 2026-03-24 Zhuo Chen , Yun Liu

We consider a data analyst's problem of purchasing data from strategic agents to compute an unbiased estimate of a statistic of interest. Agents incur private costs to reveal their data and the costs can be arbitrarily correlated with their…

Computer Science and Game Theory · Computer Science 2018-09-06 Yiling Chen , Nicole Immorlica , Brendan Lucier , Vasilis Syrgkanis , Juba Ziani

We study a simple problem of allocating common-value goods. The designer seeks to allocate the goods to as many unit-demand agents as possible without monetary transfers, while agents, who possess partial private information about the…

Theoretical Economics · Economics 2026-04-22 Hiroto Sato , Ryo Shirakawa

We consider a group of agents who can each take an irreversible costly action whose payoff depends on an unknown state. Agents learn about the state from private signals, as well as from past actions of their social network neighbors, which…

Theoretical Economics · Economics 2024-12-11 Wade Hann-Caruthers , Minghao Pan , Omer Tamuz

People are often reluctant to sell a house, or shares of stock, below the price at which they originally bought it. While this is generally not consistent with rational utility maximization, it does reflect two strong empirical regularities…

Computer Science and Game Theory · Computer Science 2021-06-02 Jon Kleinberg , Robert Kleinberg , Sigal Oren

Agents in real-world scenarios like automated driving deal with uncertainty in their environment, in particular due to perceptual uncertainty. Although, reinforcement learning is dedicated to autonomous decision-making under uncertainty…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Natalie Grabowsky , Annika Mütze , Joshua Wendland , Nils Jansen , Matthias Rottmann

Policy learning algorithms are widely used in areas such as personalized medicine and advertising to develop individualized treatment regimes. However, most methods force a decision even when predictions are uncertain, which is risky in…

Machine Learning · Computer Science 2026-01-30 Ayush Sawarni , Jikai Jin , Justin Whitehouse , Vasilis Syrgkanis

Reinforcement learners are agents that learn to pick actions that lead to high reward. Ideally, the value of a reinforcement learner's policy approaches optimality--where the optimal informed policy is the one which maximizes reward.…

Machine Learning · Computer Science 2021-05-27 Michael K. Cohen , Elliot Catt , Marcus Hutter

In many settings, multiple uninformed agents bargain simultaneously with a single informed agent in each of multiple periods. For example, workers and firms negotiate each year over salaries, and the firm has private information about the…

Theoretical Economics · Economics 2020-11-10 Quitzé Valenzuela-Stookey

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

We study the principal-agent problem with a third party that we call social planner, whose responsibility is to reconcile the conflicts of interest between the two players and induce socially optimal outcome in terms of some given social…

Computer Science and Game Theory · Computer Science 2024-11-07 Shiyun Lin , Zhihua Zhang

Negotiation is a very common interaction between automated agents. Many common negotiation protocols work with cardinal utilities, even though ordinal preferences, which only rank the outcomes, are easier to elicit from humans. In this work…

Computer Science and Game Theory · Computer Science 2023-12-18 Sefi Erlich , Noam Hazon , Sarit Kraus

This paper studies a game in which an informed sender with state-independent preferences uses verifiable messages to convince a receiver to choose an action from a finite set. We characterize the equilibrium outcomes of the game and compare…

Theoretical Economics · Economics 2025-10-10 Maria Titova , Kun Zhang

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

In a continuous-time setting where a risk-averse agent controls the drift of an output process driven by a Brownian motion, optimal contracts are linear in the terminal output; this result is well-known in a setting with moral hazard and…

Portfolio Management · Quantitative Finance 2018-07-31 N. Packham
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