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Papers
A Unified Framework for Locality in Scalable MARL
L4DC 2026
Learning-based Optimal Admission Control for Erlang-B Queuing Systems
UAI 2026
Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
COLT 2026
Achieving Õ(√T) Regret in Average-Reward POMDPs with Known Observation Models
AISTATS 2025
A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
ICML 2025
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
ICML 2025
A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
ICML 2025
Near-Optimal Sample Complexity for MDPs via Anchoring
ICML 2025
Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
ICLR 2025
Optimistic Q-learning for average reward and episodic reinforcement learning extended abstract
COLT 2025
Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL
COLT 2025
Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation
AAAI 2025
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
NeurIPS 2024
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
NeurIPS 2024
Policy Optimization for Robust Average Reward MDPs
NeurIPS 2024
Provable Policy Gradient Methods for Average-Reward Markov Potential Games
AISTATS 2024
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
AAAI 2024
Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards
NeurIPS 2024
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
ICML 2024
Solving Long-run Average Reward Robust MDPs via Stochastic Games
IJCAI 2024
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
NeurIPS 2024
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
ICML 2024
Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation
ICLR 2023
Exploration in Reward Machines with Low Regret
AISTATS 2023
Inverse Reinforcement Learning with the Average Reward Criterion
NeurIPS 2023