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As artificial agents become increasingly capable, what internal structure is *necessary* for an agent to act competently under uncertainty? Classical results show that optimal control can be *implemented* using belief states or world…

Machine Learning · Computer Science 2026-04-03 Aran Nayebi

When selling information products, the seller can provide some free partial information to change people's valuations so that the overall revenue can possibly be increased. We study the general problem of advertising information products by…

Computer Science and Game Theory · Computer Science 2021-09-24 Shuran Zheng , Yiling Chen

We study a dynamic model of Bayesian persuasion in sequential decision-making settings. An informed principal observes an external parameter of the world and advises an uninformed agent about actions to take over time. The agent takes…

Computer Science and Game Theory · Computer Science 2022-05-25 Jiarui Gan , Rupak Majumdar , Goran Radanovic , Adish Singla

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness; it is not incorporated in players' utility functions (and doing so…

Computer Science and Game Theory · Computer Science 2012-11-14 Yiling Chen , Stephen Chong , Ian A. Kash , Tal Moran , Salil Vadhan

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

We study the implementability of stable matchings in a two-sided market model with one-sided incomplete information. Firms' types are publicly known, whereas workers' types are private information. A mechanism generates a matching and…

Theoretical Economics · Economics 2025-12-23 Dinko Dimitrov , Dipjyoti Majumdar

A major achievement of mechanism design theory is a general method for the construction of truthful mechanisms called VCG (Vickrey, Clarke, Groves). When applying this method to complex problems such as combinatorial auctions, a difficulty…

Computer Science and Game Theory · Computer Science 2011-10-04 N. Nisan , A. Ronen

We consider a voting problem in which a set of agents have metric preferences over a set of alternatives, and are also partitioned into disjoint groups. Given information about the preferences of the agents and their groups, our goal is to…

Computer Science and Game Theory · Computer Science 2024-04-23 Georgios Amanatidis , Elliot Anshelevich , Christopher Jerrett , Alexandros A. Voudouris

In peer selection agents must choose a subset of themselves for an award or a prize. As agents are self-interested, we want to design algorithms that are impartial, so that an individual agent cannot affect their own chance of being…

Computer Science and Game Theory · Computer Science 2020-05-01 Nicholas Mattei , Paolo Turrini , Stanislav Zhydkov

We study principal-agent problems where a farsighted agent takes costly actions in an MDP. The core challenge in these settings is that agent's actions are hidden to the principal, who can only observe their outcomes, namely state…

Computer Science and Game Theory · Computer Science 2024-10-18 Matteo Bollini , Francesco Bacchiocchi , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

We examine hypothesis testing within a principal-agent framework, where a strategic agent, holding private beliefs about the effectiveness of a product, submits data to a principal who decides on approval. The principal employs a hypothesis…

Machine Learning · Computer Science 2025-08-06 Safwan Hossain , Yatong Chen , Yiling Chen

In bipartite matching problems, agents on two sides of a graph want to be paired according to their preferences. The stability of a matching depends on these preferences, which in uncertain environments also reflect agents' beliefs about…

Computer Science and Game Theory · Computer Science 2025-11-10 Jonathan Shaki , Jiarui Gan , Sarit Kraus

We study a truthful facility location problem where one out of $k\geq2$ available facilities must be built at a location chosen from a set of candidate ones in the interval $[0,1]$. This decision aims to accommodate a set of agents with…

Computer Science and Game Theory · Computer Science 2025-05-07 Panagiotis Kanellopoulos , Alexandros A. Voudouris

We characterize the optimal reward functions (scoring rules) that incentivize an agent to acquire information and report it truthfully to the principal. The optimal scoring rules let the agent make a simple binary bet in single-dimensional…

Computer Science and Game Theory · Computer Science 2025-10-03 Jason D. Hartline , Yingkai Li , Liren Shan , Yifan Wu

It is often argued that an agent making decisions on behalf of two or more principals who have different utility functions should adopt a {\em Pareto-optimal} policy, i.e., a policy that cannot be improved upon for one agent without making…

Artificial Intelligence · Computer Science 2017-11-02 Andrew Critch , Stuart Russell

It is typically expected that if a mechanism is truthful, then the agents would, indeed, truthfully report their private information. But why would an agent believe that the mechanism is truthful? We wish to design truthful mechanisms,…

Computer Science and Game Theory · Computer Science 2014-12-02 Simina Brânzei , Ariel D. Procaccia

It is often beneficial for agents to pool their resources in order to better accommodate fluctuations in individual demand. Many multi-round resource allocation mechanisms operate in an online manner: in each round, the agents specify their…

Computer Science and Game Theory · Computer Science 2022-08-02 Fu Li , C. Gregory Plaxton , Vaibhav B. Sinha

We study bilateral trade with interdependent values as an informed-principal problem. The mechanism-selection game has multiple equilibria that differ with respect to principal's payoff and trading surplus. We characterize the equilibrium…

Theoretical Economics · Economics 2022-02-22 Takeshi Nishimura

We study the assignment problem of objects to agents with heterogeneous preferences under distributional constraints. Each agent is associated with a publicly known type and has a private ordinal ranking over objects. We are interested in…

Data Structures and Algorithms · Computer Science 2019-05-02 Itai Ashlagi , Amin Saberi , Ali Shameli

Methods for learning optimal policies in autonomous agents often assume that the way the domain is conceptualised---its possible states and actions and their causal structure---is known in advance and does not change during learning. This…

Artificial Intelligence · Computer Science 2018-01-11 Craig Innes , Alex Lascarides , Stefano V Albrecht , Subramanian Ramamoorthy , Benjamin Rosman