value function

Discovering Reinforcement Learning Algorithms NeurIPS 2020 Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes JMLR 2020 Efficient Planning in Large MDPs with Weak Linear Function Approximation NeurIPS 2020 Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients ICML 2020 Fast Adaptation to New Environments via Policy-Dynamics Value Functions ICML 2020 Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise UAI 2020 Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning AAAI 2020 Frequency-based Search-control in Dyna ICLR 2020 Geometric Insights into the Convergence of Nonlinear TD Learning ICLR 2020 Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models ICML 2020 Gradient Regularized V-Learning for Dynamic Treatment Regimes NeurIPS 2020 Growing Action Spaces ICML 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations IJCAI 2020 Improved Vector Pruning in Exact Algorithms for Solving POMDPs UAI 2020 Learning to Plan via Deep Optimistic Value Exploration L4DC 2020 Minimax Value Interval for Off-Policy Evaluation and Policy Optimization NeurIPS 2020 Model-Augmented Actor-Critic: Backpropagating through Paths ICLR 2020 Model-Based Reinforcement Learning with Value-Targeted Regression ICML 2020 Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients AAAI 2020 Multi-Agent/Robot Deep Reinforcement Learning with Macro-Actions (Student Abstract) AAAI 2020 Neural Approximate Dynamic Programming for On-Demand Ride-Pooling AAAI 2020 Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL IJCAI 2020 Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing ICML 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020 POMDPs in Continuous Time and Discrete Spaces NeurIPS 2020