model-free reinforcement learning

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs ICML 2021 Policy Learning with Constraints in Model-free Reinforcement Learning: A Survey IJCAI 2021 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model ICLR 2021 Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021 Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning IJCAI 2021 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 Constrained Reinforcement Learning via Policy Splitting ACML 2020 Learning the model-free linear quadratic regulator via random search L4DC 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Multi-step Greedy Reinforcement Learning Algorithms ICML 2020 Observational Overfitting in Reinforcement Learning ICLR 2020 An Investigation of Model-Free Planning ICML 2019 Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning UAI 2019 Learning Representations in Model-Free Hierarchical Reinforcement Learning AAAI 2019 Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions AAAI 2019 Model-Free Linear Quadratic Control via Reduction to Expert Prediction AISTATS 2019 Dual Policy Iteration NeurIPS 2018 Q-learning with Nearest Neighbors NeurIPS 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning CoRL 2018 Simple random search of static linear policies is competitive for reinforcement learning NeurIPS 2018 Temporal Difference Models: Model-Free Deep RL for Model-Based Control ICLR 2018 Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning ICML 2017 Imagination-Augmented Agents for Deep Reinforcement Learning NeurIPS 2017 Reinforcement Learning under Model Mismatch NeurIPS 2017 Value Prediction Network NeurIPS 2017