Cover Image

Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Yang, Mondal, Washim Uddin, Aggarwal, Vaneet
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
by: Ganesh, Swetha, et al.
Published: (2024)

Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes
by: Mondal, Washim Uddin, et al.
Published: (2023)

Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
by: Bai, Qinbo, et al.
Published: (2023)

Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms
by: Aggarwal, Vaneet, et al.
Published: (2024)

Sample-Efficient Constrained Reinforcement Learning with General Parameterization
by: Mondal, Washim Uddin, et al.
Published: (2024)

Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
by: Ganesh, Swetha, et al.
Published: (2024)

Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
by: Bai, Qinbo, et al.
Published: (2024)

Last-Iterate Convergence of General Parameterized Policies in Constrained MDPs
by: Mondal, Washim Uddin, et al.
Published: (2024)

Global Convergence of Average Reward Constrained MDPs with Neural Critic and General Policy Parameterization
by: Satheesh, Anirudh, et al.
Published: (2026)

Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm
by: Xu, Yang, et al.
Published: (2025)

Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)
by: Mondal, Washim Uddin, et al.
Published: (2022)

Efficient $Q$-Learning and Actor-Critic Methods for Robust Average Reward Reinforcement Learning
by: Xu, Yang, et al.
Published: (2025)

Regret Analysis of Unichain Average Reward Constrained MDPs with General Parameterization
by: Satheesh, Anirudh, et al.
Published: (2026)

Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach
by: Ganesh, Swetha, et al.
Published: (2025)

Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
by: Ganguly, Bhargav, et al.
Published: (2023)

Sample Complexity Analysis for Constrained Bilevel Reinforcement Learning
by: Saxena, Naman, et al.
Published: (2026)

Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
by: Xu, Yang, et al.
Published: (2025)

Match or Replay: Self Imitating Proximal Policy Optimization
by: Chaudhary, Gaurav, et al.
Published: (2026)

Persistent-Transient Policy Evaluation for Markov Chains via Minimal Peripheral Quotients
by: Xu, Yang, et al.
Published: (2026)

Distributionally Robust Self Paced Curriculum Reinforcement Learning
by: Satheesh, Anirudh, et al.
Published: (2025)

Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
by: Patel, Bhrij, et al.
Published: (2024)

Breaking the Bias Barrier in Concave Multi-Objective Reinforcement Learning
by: Ganesh, Swetha, et al.
Published: (2026)

Provably Sample-Efficient Robust Reinforcement Learning with Average Reward
by: Roch, Zachary, et al.
Published: (2025)

Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm
by: Bai, Qinbo, et al.
Published: (2021)

Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
by: Chen, Zijun, et al.
Published: (2025)

Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
by: Moradipari, Ahmadreza, et al.
Published: (2023)

Primal-Only Actor Critic Algorithm for Robust Constrained Average Cost MDPs
by: Satheesh, Anirudh, et al.
Published: (2025)

On The Sample Complexity Bounds In Bilevel Reinforcement Learning
by: Gaur, Mudit, et al.
Published: (2025)

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm
by: Bai, Qinbo, et al.
Published: (2022)

Oracle-Robust Online Alignment for Large Language Models
by: Li, Zimeng, et al.
Published: (2026)

Discrete State Diffusion Models: A Sample Complexity Perspective
by: Srikanth, Aadithya, et al.
Published: (2025)

Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions
by: Chen, Jiayu, et al.
Published: (2024)

Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds
by: Zhang, Jiefu, et al.
Published: (2026)

Contrastive Cross-Modal Learning for Infusing Chest X-ray Knowledge into ECGs
by: Punyamoorty, Vineet, et al.
Published: (2025)

Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning
by: Kar, Avik, et al.
Published: (2024)

Sample Complexity of Average-Reward Q-Learning: From Single-agent to Federated Reinforcement Learning
by: Jiao, Yuchen, et al.
Published: (2026)

A Unified Framework for Analyzing Meta-algorithms in Online Convex Optimization
by: Pedramfar, Mohammad, et al.
Published: (2024)

Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model
by: Malusare, Aditya, et al.
Published: (2024)

Order-Optimal Sample Complexity of Rectified Flows
by: Sahoo, Hari Krishna, et al.
Published: (2026)

Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
by: Lan, Guangchen, et al.
Published: (2024)