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In repeated games, such as auctions, players rely on autonomous learning agents to choose their actions. We study settings in which players have their agents make monetary transfers to other agents during play at their own expense, in order…

Computer Science and Game Theory · Computer Science 2026-02-12 Yoav Kolumbus , Joe Halpern , Éva Tardos

Seamlessly interacting with humans or robots is hard because these agents are non-stationary. They update their policy in response to the ego agent's behavior, and the ego agent must anticipate these changes to co-adapt. Inspired by humans,…

Robotics · Computer Science 2020-11-16 Annie Xie , Dylan P. Losey , Ryan Tolsma , Chelsea Finn , Dorsa Sadigh

The deferred acceptance algorithm is an elegant solution to the stable matching problem that guarantees optimality and truthfulness for one side of the market. Despite these desirable guarantees, it is susceptible to strategic misreporting…

Computer Science and Game Theory · Computer Science 2020-12-09 Hadi Hosseini , Fatima Umar , Rohit Vaish

We consider Incentive Decision Processes, where a principal seeks to reduce its costs due to another agent's behavior, by offering incentives to the agent for alternate behavior. We focus on the case where a principal interacts with a…

Computer Science and Game Theory · Computer Science 2012-10-19 Sashank J. Reddi , Emma Brunskill

We consider a two-player dynamic information design problem between a principal and a receiver -- a game is played between the two agents on top of a Markovian system controlled by the receiver's actions, where the principal obtains and…

Computer Science and Game Theory · Computer Science 2024-03-20 Dengwang Tang , Vijay G. Subramanian

This paper studies contracting in the presence of externalities with a non-contractible outsider. Multiple equilibria arise from strategic symmetry between the insider agent and the outsider. To address strategic uncertainty, the principal…

Theoretical Economics · Economics 2025-09-09 Hongcheng Li

Learning to cooperate with friends and compete with foes is a key component of multi-agent reinforcement learning. Typically to do so, one requires access to either a model of or interaction with the other agent(s). Here we show how to…

Artificial Intelligence · Computer Science 2019-01-03 DJ Strouse , Max Kleiman-Weiner , Josh Tenenbaum , Matt Botvinick , David Schwab

We explore a specific parametric example of a regime change game in which a policymaker defends the status quo against a continuum of atomistic agents who seek to overthrow it. At the start of the game, the policymaker can initiate a policy…

Theoretical Economics · Economics 2025-09-08 Georgy Lukyanov

We consider the classic principal-agent model of contract theory, in which a principal designs an outcome-dependent compensation scheme to incentivize an agent to take a costly and unobservable action. When all of the model…

Computer Science and Game Theory · Computer Science 2020-08-11 Paul Dütting , Tim Roughgarden , Inbal Talgam-Cohen

Principal-agent problems model scenarios where a principal incentivizes an agent to take costly, unobservable actions through the provision of payments. Such problems are ubiquitous in several real-world applications, ranging from…

Computer Science and Game Theory · Computer Science 2025-02-27 Francesco Bacchiocchi , Jiarui Gan , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Fraud can pose a challenge in many resource allocation domains, including social service delivery and credit provision. For example, agents may misreport private information in order to gain benefits or access to credit. To mitigate this, a…

Computer Science and Game Theory · Computer Science 2026-04-29 Sanmay Das , Fang-Yi Yu , Yuang Zhang

In the classical principal-agent problem, a principal must design a contract to incentivize an agent to perform an action on behalf of the principal. We study the classical principal-agent problem in a setting where the agent can be of one…

Computer Science and Game Theory · Computer Science 2020-10-15 Guru Guruganesh , Jon Schneider , Joshua Wang

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In…

Machine Learning · Computer Science 2022-11-01 The Viet Bui , Tien Mai , Thanh H. Nguyen

We study a game between liquidity provider and liquidity taker agents interacting in an over-the-counter market, for which the typical example is foreign exchange. We show how a suitable design of parameterized families of reward functions…

Multiagent Systems · Computer Science 2023-08-02 Nelson Vadori , Leo Ardon , Sumitra Ganesh , Thomas Spooner , Selim Amrouni , Jared Vann , Mengda Xu , Zeyu Zheng , Tucker Balch , Manuela Veloso

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 consider the coupled dynamics of the adaption of network structure and the evolution of strategies played by individuals occupying the network vertices. We propose a computational model in which each agent plays a $n$-round Prisoner's…

Physics and Society · Physics 2007-11-05 Feng Fu , Xiaojie Chen , Lianghuan Liu , Long Wang

Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are…

Artificial Intelligence · Computer Science 2019-03-11 Nanda Kishore Sreenivas , Shrisha Rao

An agent choosing between various actions tends to take the one with the lowest cost. But this choice is arguably too rigid (not adaptive) to be useful in complex situations, e.g., where exploration-exploitation trade-off is relevant in…

Data Analysis, Statistics and Probability · Physics 2018-12-04 Armen E. Allahverdyan , Aram Galstyan , Ali E. Abbas , Zbigniew R. Struzik

In a framework close to the one developed by Holmstr\"om and Milgrom [44], we study the optimal contracting scheme between a Principal and several Agents. Each hired Agent is in charge of one project, and can make efforts towards managing…

Economics · Quantitative Finance 2016-05-27 Romuald Elie , Dylan Possamaï

We consider a setting where one has to organize one or several group activities for a set of agents. Each agent will participate in at most one activity, and her preferences over activities depend on the number of participants in the…

Computer Science and Game Theory · Computer Science 2014-02-03 Andreas Darmann , Edith Elkind , Sascha Kurz , Jérôme Lang , Joachim Schauer , Gerhard Woeginger
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