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We efficiently solve the optimal multi-dimensional mechanism design problem for independent bidders with arbitrary demand constraints when either the number of bidders is a constant or the number of items is a constant. In the first…

Computer Science and Game Theory · Computer Science 2011-12-20 Constantinos Daskalakis , S. Matthew Weinberg

Principal-agent problems arise when one party acts on behalf of another, leading to conflicts of interest. The economic literature has extensively studied principal-agent problems, and recent work has extended this to more complex scenarios…

Artificial Intelligence · Computer Science 2024-01-02 Omer Ben-Porat , Yishay Mansour , Michal Moshkovitz , Boaz Taitler

We consider the problem of sharing a set of indivisible goods among agents in a fair manner, namely such that the allocation is envy-free up to any good (EFX). We focus on the problem of computing an EFX allocation in the two-agent case and…

Computer Science and Game Theory · Computer Science 2023-07-18 Paul W. Goldberg , Kasper Høgh , Alexandros Hollender

Economic theory distinguishes between principal-agent settings in which the agent has a private type and settings in which the agent takes a hidden action. Many practical problems, however, involve aspects of both. For example, brand X may…

Computer Science and Game Theory · Computer Science 2021-11-24 Tal Alon , Paul Dütting , Inbal Talgam-Cohen

Algorithmic contract design studies scenarios where a principal incentivizes an agent to exert effort on her behalf. In this work, we focus on settings where the agent's type is drawn from an unknown distribution, and formalize an offline…

Computer Science and Game Theory · Computer Science 2025-01-27 Paul Duetting , Michal Feldman , Tomasz Ponitka , Ermis Soumalias

We study the problem of allocating a group of indivisible chores among agents while each chore has a binary marginal. We focus on the fairness criteria of envy-freeness up to any item (EFX) and investigate the existence of EFX allocations.…

Computer Science and Game Theory · Computer Science 2023-08-24 Biaoshuai Tao , Xiaowei Wu , Ziqi Yu , Shengwei Zhou

We consider the design of experiments to evaluate treatments that are administered by self-interested agents, each seeking to achieve the highest evaluation and win the experiment. For example, in an advertising experiment, a company wishes…

Methodology · Statistics 2015-09-18 Panos Toulis , David C. Parkes , Elery Pfeffer , James Zou

In bandit settings, optimizing long-term regret metrics requires exploration, which corresponds to sometimes taking myopically sub-optimal actions. When a long-lived principal merely recommends actions to be executed by a sequence of…

Computer Science and Game Theory · Computer Science 2026-02-25 Ramya Ramalingam , Osbert Bastani , Aaron Roth

Fairness in multi-agent systems (MAS) focuses on equitable reward distribution among agents in scenarios involving sensitive attributes such as race, gender, or socioeconomic status. This paper introduces fairness in Proximal Policy…

Multiagent Systems · Computer Science 2025-09-03 Gabriele La Malfa , Jie M. Zhang , Michael Luck , Elizabeth Black

The increasing deployment of AI is shaping the future landscape of the internet, which is set to become an integrated ecosystem of AI agents. Orchestrating the interaction among AI agents necessitates decentralized, self-sustaining…

Computer Science and Game Theory · Computer Science 2024-10-08 Dima Ivanov , Paul Dütting , Inbal Talgam-Cohen , Tonghan Wang , David C. Parkes

We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good…

Computer Science and Game Theory · Computer Science 2012-03-23 Saeed Alaei , Hu Fu , Nima Haghpanah , Jason Hartline , Azarakhsh Malekian

A reinforcement learning agent tries to maximize its cumulative payoff by interacting in an unknown environment. It is important for the agent to explore suboptimal actions as well as to pick actions with highest known rewards. Yet, in…

Machine Learning · Computer Science 2019-01-23 Reazul Hasan Russel

We study hidden-action principal-agent problems with multiple agents. Unlike previous work, we consider a general setting in which each agent has an arbitrary number of actions, and the joint action induces outcomes according to an…

Computer Science and Game Theory · Computer Science 2024-02-22 Federico Cacciamani , Martino Bernasconi , Matteo Castiglioni , Nicola Gatti

We investigate whether fairness is compatible with efficiency in economies with multi-self agents, who may not be able to integrate their multiple objectives into a single complete and transitive ranking. We adapt envy-freeness,…

Theoretical Economics · Economics 2022-04-15 Sophie Bade , Erel Segal-Halevi

When machine learning is outsourced to a rational agent, conflicts of interest might arise and severely impact predictive performance. In this work, we propose a theoretical framework for incentive-aware delegation of machine learning…

Machine Learning · Computer Science 2023-12-07 Eden Saig , Inbal Talgam-Cohen , Nir Rosenfeld

In many multiagent domains a set of agents exert effort towards a joint outcome, yet the individual effort levels cannot be easily observed. A typical example for such a scenario is routing in communication networks, where the sender can…

Computer Science and Game Theory · Computer Science 2014-01-17 Moshe Babaioff , Michal Feldman , Noam Nisan

Allocating conflicting jobs among individuals while respecting a budget constraint for each individual is an optimization problem that arises in various real-world scenarios. In this paper, we consider the situation where each individual…

Data Structures and Algorithms · Computer Science 2024-02-06 Sushmita Gupta , Pallavi Jain , A. Mohanapriya , Vikash Tripathi

This paper explores the economic interactions within modern crowdsourcing markets. In these markets, employers issue requests for tasks, platforms facilitate the recruitment of crowd workers, and workers complete tasks for monetary rewards.…

Computer Science and Game Theory · Computer Science 2026-02-03 Tian Bai , Yiding Feng , Yaohao Liu , Mengfan Ma , Mingyu Xiao

In settings where full incentive-compatibility is not available, such as core-constraint combinatorial auctions and budget-balanced combinatorial exchanges, we may wish to design mechanisms that are as incentive-compatible as possible. This…

Computer Science and Game Theory · Computer Science 2015-03-24 Benjamin Lubin

We study the repeated principal-agent bandit game, where the principal indirectly interacts with the unknown environment by proposing incentives for the agent to play arms. Most existing work assumes the agent has full knowledge of the…

Machine Learning · Computer Science 2025-06-03 Junyan Liu , Lillian J. Ratliff