Rate-Optimal Algorithm for Adversarial Linear CMDPs
cs.LG
Submitted: 2026-10-01
Updated: 2026-10-06
Sources
- Exploration-Exploitation in Constrained MDPs
- Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation
- Online Learning: A Modern Introduction Using Convex Optimization
- Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
- Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret
- Constrained Online Convex Optimization without Slater's Condition
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks