Cover Image

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kudo, Mikoto, Tanabe, Takumi, Wachi, Akifumi, Akimoto, Youhei
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computer Science and Game Theory Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Cost-Minimized Label-Flipping Poisoning Attack to LLM Alignment
by: Kusaka, Shigeki, et al.
Published: (2025)

Reinforcement Learning for Hanabi
by: Cohen, Nina, et al.
Published: (2025)

A Provable Approach for End-to-End Safe Reinforcement Learning
by: Wachi, Akifumi, et al.
Published: (2025)

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

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

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

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

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

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

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

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

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

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

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

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

The Hive Mind is a Single Reinforcement Learning Agent
by: Soma, Karthik, et al.
Published: (2024)

Analysing the Sample Complexity of Opponent Shaping
by: Fung, Kitty, et al.
Published: (2024)

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

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
by: Han, Songyang, et al.
Published: (2022)

MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning
by: Felten, Florian, et al.
Published: (2024)

Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning
by: d'Eon, Greg, et al.
Published: (2024)

Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
by: Gemp, Ian, et al.
Published: (2024)

Ev-Trust: An Evolutionarily Stable Trust Mechanism for Decentralized LLM-Based Multi-Agent Service Economies
by: Wang, Jiye, et al.
Published: (2025)

Game Theory and Multi-Agent Reinforcement Learning : From Nash Equilibria to Evolutionary Dynamics
by: De La Fuente, Neil, et al.
Published: (2024)

Bi-Level Policy Optimization with Nyström Hypergradients
by: Prakash, Arjun, et al.
Published: (2025)

Enhancing Cooperation through Selective Interaction and Long-term Experiences in Multi-Agent Reinforcement Learning
by: Ren, Tianyu, et al.
Published: (2024)

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

Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
by: Sharifi, Iman, et al.
Published: (2026)

Nash Learning from Human Feedback
by: Munos, Rémi, et al.
Published: (2023)

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

Learning Mean Field Control on Sparse Graphs
by: Fabian, Christian, et al.
Published: (2025)

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

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

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)

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

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

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

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