Copertina

Learning Mean Field Control on Sparse Graphs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Fabian, Christian, Cui, Kai, Koeppl, Heinz
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Multiagent Systems Artificial Intelligence Computer Science and Game Theory Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

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

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

Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective
di: Zaman, Muhammad Aneeq uz, et al.
Pubblicazione: (2024)

Networked Communication for Mean-Field Games with Function Approximation and Empirical Mean-Field Estimation
di: Benjamin, Patrick, et al.
Pubblicazione: (2024)

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

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

A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
di: Jiang, Haozhe, et al.
Pubblicazione: (2023)

Adaptive Network Intervention for Complex Systems: A Hierarchical Graph Reinforcement Learning Approach
di: Chen, Qiliang, et al.
Pubblicazione: (2024)

MF-OML: Online Mean-Field Reinforcement Learning with Occupation Measures for Large Population Games
di: Hu, Anran, et al.
Pubblicazione: (2024)

Preference-Based Multi-Agent Reinforcement Learning: Data Coverage and Algorithmic Techniques
di: Zhang, Natalia, et al.
Pubblicazione: (2024)

Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning
di: Kapoor, Aditya, et al.
Pubblicazione: (2024)

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning
di: Moslemi, Koorosh, et al.
Pubblicazione: (2025)

Reinforcement Learning for Hanabi
di: Cohen, Nina, et al.
Pubblicazione: (2025)

Learning to Negotiate via Voluntary Commitment
di: Zhu, Shuhui, et al.
Pubblicazione: (2025)

Nash Learning from Human Feedback
di: Munos, Rémi, et al.
Pubblicazione: (2023)

The Benefits of Power Regularization in Cooperative Reinforcement Learning
di: Li, Michelle, et al.
Pubblicazione: (2024)

Emergent Dominance Hierarchies in Reinforcement Learning Agents
di: Rachum, Ram, et al.
Pubblicazione: (2024)

Welfare and Fairness in Multi-objective Reinforcement Learning
di: Fan, Zimeng, et al.
Pubblicazione: (2022)

Learning Unanimously Acceptable Lotteries via Queries
di: Choo, Davin, et al.
Pubblicazione: (2026)

Nash Convergence of Mean-Based Learning Algorithms in First-Price Auctions
di: Deng, Xiaotie, et al.
Pubblicazione: (2021)

On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents
di: Loftin, Robert, et al.
Pubblicazione: (2024)

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

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

Offline Learning of Nash Stable Coalition Structures with Possibly Overlapping Coalitions
di: Cohen, Saar
Pubblicazione: (2026)

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning
di: Kudo, Mikoto, et al.
Pubblicazione: (2026)

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

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

AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning
di: Ekpo, Promise, et al.
Pubblicazione: (2025)

Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems
di: Yuwono, Steve, et al.
Pubblicazione: (2024)

Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
di: Li, Zun, et al.
Pubblicazione: (2023)

Scalable Neural Incentive Design with Parameterized Mean-Field Approximation
di: Corecco, Nathan, et al.
Pubblicazione: (2025)

Mechanism-Based Intelligence (MBI): Differentiable Incentives for Rational Coordination and Guaranteed Alignment in Multi-Agent Systems
di: Grassi, Stefano
Pubblicazione: (2025)

Cooperative Game-Theoretic Credit Assignment for Multi-Agent Policy Gradients via the Core
di: Ji, Mengda, et al.
Pubblicazione: (2025)

Heterogeneous Multi-Agent Bandits with Parsimonious Hints
di: Mirfakhar, Amirmahdi, et al.
Pubblicazione: (2025)

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

Procedural Fairness in Multi-Agent Bandits
di: Caiata, Joshua, et al.
Pubblicazione: (2026)

Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
di: Marris, Luke, et al.
Pubblicazione: (2021)

A Scalable Neural Network for DSIC Affine Maximizer Auction Design
di: Duan, Zhijian, et al.
Pubblicazione: (2023)

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