Value Iteration

Error Bounds of Imitating Policies and Environments NeurIPS 2020 Forethought and Hindsight in Credit Assignment NeurIPS 2020 Gamma-Nets: Generalizing Value Estimation over Timescale AAAI 2020 Harnessing Structures for Value-Based Planning and Reinforcement Learning ICLR 2020 Improved Sample Complexity for Incremental Autonomous Exploration in MDPs NeurIPS 2020 Improved Vector Pruning in Exact Algorithms for Solving POMDPs UAI 2020 Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes RSS 2020 Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020 Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020 MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control AAAI 2020 Model-Based Reinforcement Learning with Value-Targeted Regression ICML 2020 Multi-agent active perception with prediction rewards NeurIPS 2020 Multi-step Greedy Reinforcement Learning Algorithms ICML 2020 Naive Exploration is Optimal for Online LQR ICML 2020 Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020 No-regret Exploration in Contextual Reinforcement Learning UAI 2020 Off-Policy Evaluation in Partially Observable Environments AAAI 2020 Online Planning with Lookahead Policies NeurIPS 2020 On the Expressivity of Neural Networks for Deep Reinforcement Learning ICML 2020 Optimistic robust linear quadratic dual control L4DC 2020 Planning in Markov Decision Processes with Gap-Dependent Sample Complexity NeurIPS 2020 Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes AAAI 2020 POMDPs in Continuous Time and Discrete Spaces NeurIPS 2020 Reducing Sampling Error in Batch Temporal Difference Learning ICML 2020 Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States AAAI 2020