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In a delegation problem, a principal P with commitment power tries to pick one out of $n$ options. Each option is drawn independently from a known distribution. Instead of inspecting the options herself, P delegates the information…

Computer Science and Game Theory · Computer Science 2022-03-03 Pirmin Braun , Niklas Hahn , Martin Hoefer , Conrad Schecker

We study distributed composite optimization over networks: agents minimize a sum of smooth (strongly) convex functions, the agents' sum-utility, plus a nonsmooth (extended-valued) convex one. We propose a general unified algorithmic…

Optimization and Control · Mathematics 2021-08-04 Jinming Xu , Ye Tian , Ying Sun , Gesualdo Scutari

We study a principal-agent team production model. The principal hires a team of agents to participate in a common production task. The exact effort of each agent is unobservable and unverifiable, but the total production outcome (e.g. the…

Computer Science and Game Theory · Computer Science 2025-05-27 Shiliang Zuo

Iterated coopetitive games capture the situation when one must efficiently balance between cooperation and competition with the other agents over time in order to win the game (e.g., to become the player with highest total utility).…

Computer Science and Game Theory · Computer Science 2022-03-11 Shivakumar Mahesh , Nicholas Bishop , Le Cong Dinh , Long Tran-Thanh

Networked public goods games model scenarios in which self-interested agents decide whether or how much to invest in an action that benefits not only themselves, but also their network neighbors. Examples include vaccination, security…

Computer Science and Game Theory · Computer Science 2021-09-03 David Kempe , Sixie Yu , Yevgeniy Vorobeychik

Coalition formation explores how to partition a set of $n$ agents into disjoint coalitions according to their preferences. We consider a cardinal utility model with an additively separable aggregation of preferences and study the online…

Computer Science and Game Theory · Computer Science 2025-03-11 Martin Bullinger , René Romen

Multiagent reinforcement learning algorithms have not been widely adopted in large scale environments with many agents as they often scale poorly with the number of agents. Using mean field theory to aggregate agents has been proposed as a…

Multiagent Systems · Computer Science 2022-04-14 Sriram Ganapathi Subramanian , Matthew E. Taylor , Mark Crowley , Pascal Poupart

We obtain global, non-asymptotic convergence guarantees for independent learning algorithms in competitive reinforcement learning settings with two agents (i.e., zero-sum stochastic games). We consider an episodic setting where in each…

Machine Learning · Computer Science 2021-01-13 Constantinos Daskalakis , Dylan J. Foster , Noah Golowich

In this paper, we consider a general distributed system with multiple agents who select and then implement actions in the system. The system has an operator with a centralized objective. The agents, on the other hand, are selfinterested and…

Computer Science and Game Theory · Computer Science 2020-01-15 Donya Ghavidel , Pratyush Chakraborty , Enrique Baeyens , Vijay Gupta , Pramod P. Khargonekar

It is an amazing fact that remarkably complex behaviors could emerge from a large collection of very rudimentary dynamical agents through very simple local interactions. However, it still remains elusive on how to design these local…

Multiagent Systems · Computer Science 2011-01-13 Mohammad Karimadini , Hai Lin

Learning to adapt and make real-time informed decisions in a dynamic and complex environment is a challenging problem. Monopoly is a popular strategic board game that requires players to make multiple decisions during the game.…

Machine Learning · Computer Science 2022-04-07 Trevor Bonjour , Marina Haliem , Aala Alsalem , Shilpa Thomas , Hongyu Li , Vaneet Aggarwal , Mayank Kejriwal , Bharat Bhargava

Winners-take-all situations introduce an incentive for agents to diversify their behavior, since doing so will result in splitting an eventual price with fewer people. At the same time, when the payoff of a process depends on a parameter…

Computer Science and Game Theory · Computer Science 2019-06-11 Abel Molina

Impartial selection problems are concerned with the selection of one or more agents from a set based on mutual nominations from within the set. To avoid strategic nominations of the agents, the axiom of impartiality requires that the…

Computer Science and Game Theory · Computer Science 2024-10-01 Javier Cembrano , Max Klimm , Arturo Merino

The lack of cooperation can easily result in inequality among members of a society, which provides an increasing gap between individual incomes. To tackle this issue, we introduce an incentive mechanism based on individual strategies and…

Physics and Society · Physics 2025-01-24 Luo-Luo Jiang , Yi-Ming Li , Wen-Jing Li , Attila Szolnoki

While discounted payoff games and classic games that reduce to them, like parity and mean-payoff games, are symmetric, their solutions are not. We have taken a fresh view on the properties that optimal solutions need to have, and devised a…

Data Structures and Algorithms · Computer Science 2026-03-11 Daniele Dell'Erba , Arthur Dumas , Sven Schewe

We study the classic divide-and-choose method for equitably allocating divisible goods between two players who are rational, self-interested Bayesian agents. The players have additive values for the goods. The prior distributions on those…

Computer Science and Game Theory · Computer Science 2024-10-22 Jamie Tucker-Foltz , Richard Zeckhauser

We introduce a model of competing agents in a prophet setting, where rewards arrive online, and decisions are made immediately and irrevocably. The rewards are unknown from the outset, but they are drawn from a known probability…

Computer Science and Game Theory · Computer Science 2021-07-02 Tomer Ezra , Michal Feldman , Ron Kupfer

This paper studies a dynamic screening model in which a principal hires an agent with limited liability. The agent's private cost of working is an i.i.d. draw from a continuous distribution. His working status is publicly observable. The…

Theoretical Economics · Economics 2025-11-26 Yijun Liu

Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing, multi-robot coordination and information gathering scenarios…

Artificial Intelligence · Computer Science 2011-11-02 Claudia V. Goldman , Shlomo Zilberstein

We consider quadratic, nonmonotone generalized Nash equilibrium problems with symmetric interactions among the agents. Albeit this class of games is known to admit a potential function, its formal expression can be unavailable in several…

Optimization and Control · Mathematics 2022-03-31 Filippo Fabiani , Andrea Simonetto , Paul J. Goulart
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