value estimation

The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation ICML 2023 Toward Efficient Gradient-Based Value Estimation ICML 2023 Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL NeurIPS 2023 Controlling Underestimation Bias in Reinforcement Learning via Quasi-median Operation AAAI 2022 Efficient Continuous Control with Double Actors and Regularized Critics AAAI 2022 Learning Pseudometric-based Action Representations for Offline Reinforcement Learning ICML 2022 Model-Value Inconsistency as a Signal for Epistemic Uncertainty ICML 2022 Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks ICML 2022 Search-based Reinforcement Learning through Bandit Linear Optimization IJCAI 2022 Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks AAAI 2021 A Minimalist Approach to Offline Reinforcement Learning NeurIPS 2021 Average-Reward Reinforcement Learning with Trust Region Methods IJCAI 2021 Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning NeurIPS 2021 Deeply-Debiased Off-Policy Interval Estimation ICML 2021 Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction AAAI 2021 Loop Estimator for Discounted Values in Markov Reward Processes AAAI 2021 Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation WACV 2021 Self-correcting Q-learning AAAI 2021 Attentive Experience Replay AAAI 2020 Gamma-Nets: Generalizing Value Estimation over Timescale AAAI 2020 ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search AAAI 2019 How to Combine Tree-Search Methods in Reinforcement Learning AAAI 2019 Multi-Task Deep Reinforcement Learning with PopArt AAAI 2019 Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning NeurIPS 2019 Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning NeurIPS 2017