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We consider a dynamic moral hazard problem between a principal and an agent, where the sole instrument the principal has to incentivize the agent is the disclosure of information. The principal aims at maximizing the (discounted) number of…

Theoretical Economics · Economics 2021-03-09 Wei Zhao , Claudio Mezzetti , Ludovic Renou , Tristan Tomala

A natural way to design a negotiation dialogue system is via self-play RL: train an agent that learns to maximize its performance by interacting with a simulated user that has been designed to imitate human-human dialogue data. Although…

Computation and Language · Computer Science 2023-10-24 Kushal Chawla , Ian Wu , Yu Rong , Gale M. Lucas , Jonathan Gratch

Privacy concerns have led to the development of privacy-preserving approaches for learning models from sensitive data. Yet, in practice, even models learned with privacy guarantees can inadvertently memorize unique training examples or leak…

Machine Learning · Statistics 2019-11-11 Mario Diaz , Peter Kairouz , Jiachun Liao , Lalitha Sankar

We study mechanism design when agents may have hidden secondary goals which will manifest as non-trivial preferences among outcomes for which their primary utility is the same. We show that in such cases, a mechanism is robust against…

Computer Science and Game Theory · Computer Science 2023-07-25 Renato Paes Leme , Jon Schneider , Hanrui Zhang

We analyze a principal-agent procurement problem in which the principal (she) is unaware some of the marginal cost types of the agent (he). Communication arises naturally as some types of the agent may have an incentive to raise the…

Theoretical Economics · Economics 2025-10-27 Alejandro Francetich , Burkhard C. Schipper

Fairness is a desirable and crucial property of many protocols that handle, for instance, exchanges of message. It states that if at least one agent engaging in the protocol is honest, then either the protocol will unfold correctly and…

Computer Science and Game Theory · Computer Science 2024-11-01 Léonard Brice , Jean-François Raskin , Mathieu Sassolas , Guillaume Scerri , Marie van den Bogaard

Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other…

Artificial Intelligence · Computer Science 2018-02-12 Stefano V. Albrecht , Peter Stone

Computer-aided design of molecules has the potential to disrupt the field of drug and material discovery. Machine learning, and deep learning, in particular, have been topics where the field has been developing at a rapid pace.…

Machine Learning · Computer Science 2022-08-08 Luca A. Thiede , Mario Krenn , AkshatKumar Nigam , Alan Aspuru-Guzik

Agents that learn to select optimal actions represent a prominent focus of the sequential decision-making literature. In the face of a complex environment or constraints on time and resources, however, aiming to synthesize such an optimal…

Machine Learning · Computer Science 2021-06-23 Dilip Arumugam , Benjamin Van Roy

We study a mechanism-design problem in which spiteful agents strive to not only maximize their rewards but also, contingent upon their own payoff levels, seek to lower the opponents' rewards. We characterize all individually rational (IR)…

Computer Science and Game Theory · Computer Science 2025-12-02 Aditya Aradhye , David Lagziel , Eilon Solan

The increased complexity of state-of-the-art reinforcement learning (RL) algorithms have resulted in an opacity that inhibits explainability and understanding. This has led to the development of several post-hoc explainability methods that…

Machine Learning · Computer Science 2022-03-25 Charl Maree , Christian Omlin

A contract is an economic tool used by a principal to incentivize one or more agents to exert effort on her behalf, by defining payments based on observable performance measures. A key challenge addressed by contracts -- known in economics…

Computer Science and Game Theory · Computer Science 2024-12-24 Paul Duetting , Michal Feldman , Inbal Talgam-Cohen

This paper studies the optimal mechanism to motivate effort in a dynamic principal-agent model without transfers. An agent is engaged in a task with uncertain future rewards and can quit at any time. The principal knows the reward and…

Theoretical Economics · Economics 2026-01-16 Chang Liu

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

Decisions in organizations are about evaluating alternatives and choosing the one that would best serve organizational goals. To the extent that the evaluation of alternatives could be formulated as a predictive task with appropriate…

Human-Computer Interaction · Computer Science 2022-06-30 Charles Wan , Rodrigo Belo , Leid Zejnilović

Service providers commonly provide only a fixed catalog of services to their clients. Both clients and service providers can benefit from service negotiation, in which a client makes a query for a specific service, and the provider counters…

Logic in Computer Science · Computer Science 2023-07-07 Glenn Bruns , Mauricio Cortes

We study strategic interactions in a broker-mediated market in which agents learn and exploit each other's private information. A broker provides liquidity to an informed trader and to noise traders while managing inventory in a lit market.…

Trading and Market Microstructure · Quantitative Finance 2026-01-21 Alif Aqsha , Fayçal Drissi , Leandro Sánchez-Betancourt

Modelling other agents' behaviors plays an important role in decision models for interactions among multiple agents. To optimise its own decisions, a subject agent needs to model what other agents act simultaneously in an uncertain…

Artificial Intelligence · Computer Science 2022-03-08 Yinghui Pan , Hanyi Zhang , Yifeng Zeng , Biyang Ma , Jing Tang , Zhong Ming

In many real-world scenarios where extrinsic rewards to the agent are extremely sparse, curiosity has emerged as a useful concept providing intrinsic rewards that enable the agent to explore its environment and acquire information to…

Machine Learning · Computer Science 2021-04-27 Jivat Neet Kaur , Yiding Jiang , Paul Pu Liang

Persuasion studies how a principal can influence agents' decisions via strategic information revelation --- often described as a signaling scheme --- in order to yield the most desirable equilibrium outcome. Recently, there has been a large…

Computer Science and Game Theory · Computer Science 2019-10-22 Haifeng Xu
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