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In this paper we present results and analyses of a class of games in which heterogeneous agents are rewarded for being in a minority group. Each agent possesses a number of fixed strategies each of which are predictors of the next minority…

adap-org · Physics 2007-05-23 Radu Manuca , Yi Li , Rick Riolo , Robert Savit

We study the problem of selection in the context of Bayesian persuasion. We are given multiple agents with hidden values (or quality scores), to whom resources must be allocated by a welfare-maximizing decision-maker. An intermediary with…

Computer Science and Game Theory · Computer Science 2025-11-18 Yannan Bai , Kamesh Munagala , Yiheng Shen , Davidson Zhu

Multiplayer games with selfish agents naturally occur in the design of distributed and embedded systems. As the goals of selfish agents are usually neither equivalent nor antagonistic to each other, such games are non zero-sum games. We…

Computer Science and Game Theory · Computer Science 2012-12-19 Thomas Brihaye , Julie De Pril , Sven Schewe

In this article we study the behavior of a group of economic agents in the context of cooperative game theory, interacting according to rules based on the Potts Model with suitable modifications. Each agent can be thought of as belonging to…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Roberto da Silva , Alexandre Tavares Baraviera , Silvio R. Dahmen

How do different alliance mechanisms compare? In this work, we analyze various methods of forming an alliance in the Coalitional General Lotto game, a simple model of competitive resource allocation. In the game, Players 1 and 2…

Computer Science and Game Theory · Computer Science 2026-01-30 Vade Shah , Jason R. Marden

It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite trend: LLMs with stronger reasoning capabilities behave _less_ cooperatively in mixed-motive…

Computer Science and Game Theory · Computer Science 2026-04-17 Emanuel Tewolde , Xiao Zhang , David Guzman Piedrahita , Vincent Conitzer , Zhijing Jin

This paper investigates the potential benefits of cooperation in scenarios where finitely many agents compete for shared resources, leading to congestion and thereby reduced rewards. By appropriate coordination the members of the…

Computer Science and Game Theory · Computer Science 2024-10-10 Riya Sultana , Veeraruna Kavitha

Imitation is widely observed in populations of decision-making agents. Using our recent convergence results for asynchronous imitation dynamics on networks, we consider how such networks can be efficiently driven to a desired equilibrium…

Computer Science and Game Theory · Computer Science 2017-04-17 James Riehl , Pouria Ramazi , Ming Cao

This paper investigates the implementation and performance of a decentralized information transmission mechanism in game with complete or incomplete games. We propose a mechanism that realizes irrational correlated equilibria or irrational…

Theoretical Economics · Economics 2025-11-12 Shitong Wang

We introduce and study an evolutionary complementarity game where in each round a player of population 1 is paired with a member of population 2. The game is symmetric, and each player tries to obtain an advantageous deal, but when one of…

Adaptation and Self-Organizing Systems · Physics 2015-06-26 Juergen Jost , Wei Li

In sports competitions, teams can manipulate the result by, for instance, throwing games. We show that we can decide how to manipulate round robin and cup competitions, two of the most popular types of sporting competitions in polynomial…

Artificial Intelligence · Computer Science 2012-04-18 Tyrel Russell , Toby Walsh

Many economic games and machine learning approaches can be cast as competitive optimization problems where multiple agents are minimizing their respective objective function, which depends on all agents' actions. While gradient descent is a…

Machine Learning · Computer Science 2021-11-17 Jeffrey Ma , Alistair Letcher , Florian Schäfer , Yuanyuan Shi , Anima Anandkumar

While advances in multi-agent learning have enabled the training of increasingly complex agents, most existing techniques produce a final policy that is not designed to adapt to a new partner's strategy. However, we would like our AI agents…

Machine Learning · Computer Science 2022-01-06 Andy Shih , Stefano Ermon , Dorsa Sadigh

Agents rarely act in isolation -- their behavioral history, in particular, is public to others. We seek a non-asymptotic understanding of how a leader agent should shape this history to its maximal advantage, knowing that follower agent(s)…

Computer Science and Game Theory · Computer Science 2019-05-29 Vidya Muthukumar , Anant Sahai

This work shows that the formation of a finite number of coalitions in a nonatomic network congestion game benefits everyone. At the equilibrium of the composite game played by coalitions and individuals, the average cost to each coalition…

Computer Science and Game Theory · Computer Science 2015-03-20 Cheng Wan

Cooperation is fundamental for society's viability, as it enables the emergence of structure within heterogeneous groups that seek collective well-being. However, individuals are inclined to defect in order to benefit from the group's…

Multiagent Systems · Computer Science 2026-02-10 Yao-hua Franck Xu , Tayeb Lemlouma , Arnaud Braud , Jean-Marie Bonnin

Optimization under uncertainty is a fundamental problem in learning and decision-making, particularly in multi-agent systems. Previously, Feldman, Kalai, and Tennenholtz [2010] demonstrated the ability to efficiently compete in repeated…

Computer Science and Game Theory · Computer Science 2026-01-29 Daniel Ablin , Alon Cohen

In this paper we propose a method that learns to play Pac-Man. We define a set of high-level observation and action modules. Actions are temporally extended, and multiple action modules may be in effect concurrently. A decision of the agent…

Machine Learning · Computer Science 2007-05-23 Istvan Szita , Andras Lorincz

A negotiating team is a group of two or more agents who join together as a single negotiating party because they share a common goal related to the negotiation. Since a negotiating team is composed of several stakeholders, represented as a…

Computer Science and Game Theory · Computer Science 2021-08-03 Leora Schmerler , Noam Hazon

Concurrent games with a fixed number of agents have been thoroughly studied, with various solution concepts and objectives for the agents. In this paper, we consider concurrent games with an arbitrary number of agents, and study the problem…

Logic in Computer Science · Computer Science 2020-10-01 Nathalie Bertrand , Patricia Bouyer , Anirban Majumdar