conftrace_

average reward

29 papers

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Co-occurring keywords

markov decision process (790) reinforcement learning (4352) regret bound (1926) sample complexity (1169) average-reward mdp (10) policy learning (702) policy gradient (520) policy optimization (657) model-free reinforcement learning (63) reward shaping (110)

Papers

Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation AAAI 2025
Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024
Reinforcement Learning with LTL and $\omega$-Regular Objectives via Optimality-Preserving Translation to Average Rewards NIPS 2024
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes AAAI 2024
Policy Optimization for Robust Average Reward MDPs NIPS 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 NIPS 2024
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm NIPS 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NIPS 2024
Inverse Reinforcement Learning with the Average Reward Criterion NIPS 2023
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms NIPS 2023
Off-Policy Average Reward Actor-Critic with Deterministic Policy Search ICML 2023
Exploration in Reward Machines with Low Regret AISTATS 2023
Robust Average-Reward Markov Decision Processes AAAI 2023
Influencing Long-Term Behavior in Multiagent Reinforcement Learning NIPS 2022
A Provably-Efficient Model-Free Algorithm for Infinite-Horizon Average-Reward Constrained Markov Decision Processes AAAI 2022
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks AAAI 2021
Average-Reward Learning and Planning with Options NIPS 2021
Optimal Policies Tend To Seek Power NIPS 2021
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward NIPS 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards ICML 2020
Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward UAI 2020
Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract) AAAI 2020
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards NIPS 2019