Methods

To Follow or not to Follow: Selective Imitation Learning from Observations CoRL 2019 Towards Better Interpretability in Deep Q-Networks AAAI 2019 Towards Governing Agent’s Efficacy: Action-Conditional $β$-VAE for Deep Transparent Reinforcement Learning ACML 2019 Towards Interpretable Reinforcement Learning Using Attention Augmented Agents NeurIPS 2019 Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling NeurIPS 2019 Towards Sequence-to-Sequence Reinforcement Learning for Constraint Solving with Constraint-Based Local Search AAAI 2019 Trajectory-Based Off-Policy Deep Reinforcement Learning ICML 2019 Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods CoRL 2019 Transfer in Deep Reinforcement Learning Using Knowledge Graphs EMNLP 2019 Transfer of Samples in Policy Search via Multiple Importance Sampling ICML 2019 Transfer of Temporal Logic Formulas in Reinforcement Learning IJCAI 2019 Truly Batch Apprenticeship Learning with Deep Successor Features IJCAI 2019 Truly Proximal Policy Optimization UAI 2019 Trust Region Evolution Strategies AAAI 2019 Trust Region-Guided Proximal Policy Optimization NeurIPS 2019 Two-Timescale Networks for Nonlinear Value Function Approximation ICLR 2019 Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples NeurIPS 2019 Understanding the Impact of Entropy on Policy Optimization ICML 2019 Unified Policy Optimization for Robust Reinforcement Learning ACML 2019 Universal Successor Features Approximators ICLR 2019 Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts IJCAI 2019 Unsupervised Context Rewriting for Open Domain Conversation EMNLP 2019 Unsupervised Control Through Non-Parametric Discriminative Rewards ICLR 2019 Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning NeurIPS 2019 Using Natural Language for Reward Shaping in Reinforcement Learning IJCAI 2019