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Self-play is a technique for machine learning in multi-agent systems where a learning algorithm learns by interacting with copies of itself. Self-play is useful for generating large quantities of data for learning, but has the drawback that…

Computer Science and Game Theory · Computer Science 2023-11-30 Revan MacQueen , James R. Wright

We consider a two-player zero-sum deterministic differential game where each player uses both continuous and impulse controls in infinite-time horizon. We assume that the impulses supposed to be of general term and the costs depend on the…

Optimization and Control · Mathematics 2022-09-26 Brahim El Asri , Hafid Lalioui

Zero-sum games have long guided artificial intelligence research, since they possess both a rich strategy space of best-responses and a clear evaluation metric. What's more, competition is a vital mechanism in many real-world multi-agent…

Computer Science and Game Theory · Computer Science 2020-03-03 Edward Hughes , Thomas W. Anthony , Tom Eccles , Joel Z. Leibo , David Balduzzi , Yoram Bachrach

Game theory is a very profound study on distributed decision-making behavior and has been extensively developed by many scholars. However, many existing works rely on certain strict assumptions such as knowing the opponent's private…

Computer Science and Game Theory · Computer Science 2020-04-21 Kuo Chun Tsai , Zhu Han

We present a new approach to solving games with a countably or uncountably infinite number of players. Such games are often used to model multiagent systems with a large number of agents. The latter are frequently encountered in economics,…

Computer Science and Game Theory · Computer Science 2025-01-17 Carlos Martin , Tuomas Sandholm

To learn good joint policies for multi-agent collaboration with imperfect information remains a fundamental challenge. While for two-player zero-sum games, coordinate-ascent approaches (optimizing one agent's policy at a time, e.g.,…

Machine Learning · Computer Science 2020-12-08 Yuandong Tian , Qucheng Gong , Tina Jiang

We introduce, to our knowledge, the first direct second-order method for computing Nash equilibria in two-player zero-sum games. To do so, we construct a Douglas-Rachford-style splitting formulation, which we then solve with a semi-smooth…

Computer Science and Game Theory · Computer Science 2025-12-16 David Yang , Yuan Gao , Tianyi Lin , Christian Kroer

In this paper we study team-symmetric games with $m\ge 2$ teams. Players within a team have symmetric identity and have a common payoff function. We show that team-symmetric games always have a team-symmetric Nash equilibrium. We develop…

Multiagent Systems · Computer Science 2026-05-14 Duan-Shin Lee , Yu-Hsiu Hung

Public goods games study the incentives of individuals to contribute to a public good and their behaviors in equilibria. In this paper, we examine a specific type of public goods game where players are networked and each has binary actions,…

Computer Science and Game Theory · Computer Science 2022-04-04 Sixie Yu , Kai Zhou , P. Jeffrey Brantingham , Yevgeniy Vorobeychik

In this paper, we prove the existence of classical solutions for second order stationary mean-field game systems. These arise in ergodic (mean-field) optimal control, convex degenerate problems in calculus of variations, and in the study of…

Analysis of PDEs · Mathematics 2015-03-24 Edgard A. Pimentel , Vardan Voskanyan

The paper is concerned with a two-player nonzero-sum differential game in the case when players are informed about the current position. We consider the game in control with guide strategies first proposed by Krasovskii and Subbotin. The…

Optimization and Control · Mathematics 2013-06-11 Yurii Averboukh

Learning problems commonly exhibit an interesting feedback mechanism wherein the population data reacts to competing decision makers' actions. This paper formulates a new game theoretic framework for this phenomenon, called "multi-player…

Computer Science and Game Theory · Computer Science 2022-04-08 Adhyyan Narang , Evan Faulkner , Dmitriy Drusvyatskiy , Maryam Fazel , Lillian J. Ratliff

We show by counterexample that policy-gradient algorithms have no guarantees of even local convergence to Nash equilibria in continuous action and state space multi-agent settings. To do so, we analyze gradient-play in N-player general-sum…

Machine Learning · Computer Science 2019-12-18 Eric Mazumdar , Lillian J. Ratliff , Michael I. Jordan , S. Shankar Sastry

State-of-the-art methods for solving 2-player zero-sum imperfect information games rely on linear programming or regret minimization, though not on dynamic programming (DP) or heuristic search (HS), while the latter are often at the core of…

Artificial Intelligence · Computer Science 2022-10-27 Aurélien Delage , Olivier Buffet , Jilles S. Dibangoye , Abdallah Saffidine

This paper investigates a population-based training regime based on game-theoretic principles called Policy-Spaced Response Oracles (PSRO). PSRO is general in the sense that it (1) encompasses well-known algorithms such as fictitious play…

Policy gradient methods have become a staple of any single-agent reinforcement learning toolbox, due to their combination of desirable properties: iterate convergence, efficient use of stochastic trajectory feedback, and theoretically-sound…

Computer Science and Game Theory · Computer Science 2025-07-10 Mingyang Liu , Gabriele Farina , Asuman Ozdaglar

Nash Equilibrium (NE) is the canonical solution concept of game theory, which provides an elegant tool to understand the rationalities. Though mixed strategy NE exists in any game with finite players and actions, computing NE in two- or…

Computer Science and Game Theory · Computer Science 2024-05-07 Xinrun Wang , Chang Yang , Shuxin Li , Pengdeng Li , Xiao Huang , Hau Chan , Bo An

We consider a general-sum N-player linear-quadratic game with stochastic dynamics over a finite horizon and prove the global convergence of the natural policy gradient method to the Nash equilibrium. In order to prove the convergence of the…

Optimization and Control · Mathematics 2022-08-16 Ben Hambly , Renyuan Xu , Huining Yang

We consider second-order ergodic Mean-Field Games systems in the whole space $\mathbb{R}^N$ with coercive potential and aggregating nonlocal coupling, defined in terms of a Riesz interaction kernel. These MFG systems describe Nash…

Analysis of PDEs · Mathematics 2023-05-01 Chiara Bernardini , Annalisa Cesaroni

Strategic interactions can be represented more concisely, and analyzed and solved more efficiently, if we are aware of the symmetries within the multiagent system. Symmetries also have conceptual implications, for example for equilibrium…

Computer Science and Game Theory · Computer Science 2025-03-03 Emanuel Tewolde , Brian Hu Zhang , Caspar Oesterheld , Tuomas Sandholm , Vincent Conitzer