:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Smithline, Gabriel, Nivison, Scott
Format:	Preprint
Published:	2025
Subjects:	Multiagent Systems Computer Science and Game Theory Machine Learning
Online Access:	https://arxiv.org/abs/2510.10830
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data-Augmented Game Starts for Accelerating Self-Play Exploration in Imperfect Information Games
by: Lanier, JB, et al.
Published: (2026)

Grasper: A Generalist Pursuer for Pursuit-Evasion Problems
by: Li, Pengdeng, et al.
Published: (2024)

Performative Prediction on Games and Mechanism Design
by: Góis, António, et al.
Published: (2024)

Independent Learning in Constrained Markov Potential Games
by: Jordan, Philip, et al.
Published: (2024)

Observation Interference in Partially Observable Assistance Games
by: Emmons, Scott, et al.
Published: (2024)

Fair Contracts in Principal-Agent Games with Heterogeneous Types
by: Tłuczek, Jakub, et al.
Published: (2025)

On the Power of Perturbation under Sampling in Solving Extensive-Form Games
by: Masaka, Wataru, et al.
Published: (2025)

Tractable Equilibrium Computation in Markov Games through Risk Aversion
by: Mazumdar, Eric, et al.
Published: (2024)

Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation
by: Jordan, Philip, et al.
Published: (2025)

Grouped Satisficing Paths in Pure Strategy Games: a Topological Perspective
by: Fu, Yanqing, et al.
Published: (2025)

Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
by: Peng, Nianli, et al.
Published: (2024)

Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game Theory
by: Buratto, Alessandro, et al.
Published: (2025)

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
by: Wang, Jianhong, et al.
Published: (2025)

Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics
by: Jordan, Philip, et al.
Published: (2026)

Independent Policy Mirror Descent for Markov Potential Games: Scaling to Large Number of Players
by: Alatur, Pragnya, et al.
Published: (2024)

Convex Markov Games and Beyond: New Proof of Existence, Characterization and Learning Algorithms for Nash Equilibria
by: Barakat, Anas, et al.
Published: (2026)

Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
by: Shi, Chengshuai, et al.
Published: (2024)

Aggregate Fictitious Play for Learning in Anonymous Polymatrix Games (Extended Version)
by: Kara, Semih, et al.
Published: (2025)

Choose Your Battles: Distributed Learning Over Multiple Tug of War Games
by: Chandak, Siddharth, et al.
Published: (2025)

Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning
by: Wu, Zida, et al.
Published: (2024)

Auto-Encoding Bayesian Inverse Games
by: Liu, Xinjie, et al.
Published: (2024)

Evaluating LLMs in Open-Source Games
by: Sistla, Swadesh, et al.
Published: (2025)

Solving Zero-Sum Convex Markov Games
by: Kalogiannis, Fivos, et al.
Published: (2025)

Offline Fictitious Self-Play for Competitive Games
by: Chen, Jingxiao, et al.
Published: (2024)

Aspiration-based Perturbed Learning Automata in Games with Noisy Utility Measurements. Part A: Stochastic Stability in Non-zero-Sum Games
by: Chasparis, Georgios C.
Published: (2025)

Bounded Rationality Equilibrium Learning in Mean Field Games
by: Eich, Yannick, et al.
Published: (2024)

Learning Optimal Tax Design in Nonatomic Congestion Games
by: Cui, Qiwen, et al.
Published: (2024)

Learning from Delayed Feedback in Games via Extra Prediction
by: Fujimoto, Yuma, et al.
Published: (2025)

Online Learning of Counter Categories and Ratings in PvP Games
by: Lin, Chiu-Chou, et al.
Published: (2025)

Linear Convergence in Games with Delayed Feedback via Extra Prediction
by: Fujimoto, Yuma, et al.
Published: (2026)

RuleSmith: Multi-Agent LLMs for Automated Game Balancing
by: Zeng, Ziyao, et al.
Published: (2026)

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory
by: Çelikok, Mustafa Mert, et al.
Published: (2024)

Policy Iteration for Two-Player General-Sum Stochastic Stackelberg Games
by: Kudo, Mikoto, et al.
Published: (2024)

ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games
by: Lei, Shiqi, et al.
Published: (2024)

Stackelberg Learning from Human Feedback: Preference Optimization as a Sequential Game
by: Pásztor, Barna, et al.
Published: (2025)

Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
by: Fabian, Christian, et al.
Published: (2024)

A Single Online Agent Can Efficiently Learn Mean Field Games
by: Zhang, Chenyu, et al.
Published: (2024)

Policy Optimization finds Nash Equilibrium in Regularized General-Sum LQ Games
by: Zaman, Muhammad Aneeq uz, et al.
Published: (2024)

Limit-Computable Grains of Truth for Arbitrary Computable Extensive-Form (Un)Known Games
by: Wyeth, Cole, et al.
Published: (2025)

Policy Optimization and Multi-agent Reinforcement Learning for Mean-variance Team Stochastic Games
by: Hu, Junkai, et al.
Published: (2025)