Interactive Distributionally Robust Multi-Agent Learning with General Function Approximation
cs.LG, cs.AI
Submitted: 2026-09-25
Updated: 2026-09-25
Terminology
Sources
- Wasserstein Robust Reinforcement Learning
- Towards Minimax Optimality of Model-based Robust Reinforcement Learning
- Bilinear Classes: A Structural Framework for Provable Generalization in RL
- Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
- The Statistical Complexity of Interactive Decision Making
- Online Robust Reinforcement Learning with General Function Approximation
- Towards General Function Approximation in Zero-Sum Markov Games
- Minimax-Optimal Multi-Agent Robust Reinforcement Learning
- Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning
- Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation
- Representation Learning for General-sum Low-rank Markov Games
- Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
- Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
- EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
- Distributionally Robust Markov Games with Average Reward
- Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
- Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
- Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty
- Robust Reinforcement Learning using Adversarial Populations
- Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes
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