value function

Importance Resampling for Off-policy Prediction NeurIPS 2019 Mapping State Space using Landmarks for Universal Goal Reaching NeurIPS 2019 MAVEN: Multi-Agent Variational Exploration NeurIPS 2019 Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift AAAI 2019 Planning with Expectation Models IJCAI 2019 Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control ICLR 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NeurIPS 2019 Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update NeurIPS 2019 Scale-free adaptive planning for deterministic dynamics & discounted rewards ICML 2019 Separating value functions across time-scales ICML 2019 Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs AAAI 2019 Surveys without Questions: A Reinforcement Learning Approach AAAI 2019 The Expected-Length Model of Options IJCAI 2019 The Value Function Polytope in Reinforcement Learning ICML 2019 Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds ICML 2019 Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning NeurIPS 2019 Addressing Function Approximation Error in Actor-Critic Methods ICML 2018 A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation COLT 2018 A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning IJCAI 2018 Bayesian RL for Goal-Only Rewards CoRL 2018 Beyond the One-Step Greedy Approach in Reinforcement Learning ICML 2018 Fast deep reinforcement learning using online adjustments from the past NeurIPS 2018 Feedback-Based Tree Search for Reinforcement Learning ICML 2018 Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator ICML 2018 Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning ICLR 2018