Policy Learning

Model-Based Reinforcement Learning with Value-Targeted Regression ICML 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Modeling Protagonist Emotions for Emotion-Aware Storytelling EMNLP 2020 Momentum-Based Policy Gradient Methods ICML 2020 Monte-Carlo Tree Search as Regularized Policy Optimization ICML 2020 Multi-Agent Actor-Critic with Hierarchical Graph Attention Network AAAI 2020 Munchausen Reinforcement Learning NeurIPS 2020 Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes NeurIPS 2020 No-regret Exploration in Contextual Reinforcement Learning UAI 2020 No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020 Off-Policy Actor-Critic with Shared Experience Replay ICML 2020 Off-Policy Imitation Learning from Observations NeurIPS 2020 Online learning with dynamics: A minimax perspective NeurIPS 2020 Online Meta-Critic Learning for Off-Policy Actor-Critic Methods NeurIPS 2020 Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL IJCAI 2020 On Reward-Free Reinforcement Learning with Linear Function Approximation NeurIPS 2020 On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020 On the Role of Weight Sharing During Deep Option Learning AAAI 2020 Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020 Optimistic Policy Optimization with Bandit Feedback ICML 2020 Optimistic robust linear quadratic dual control L4DC 2020 Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning AISTATS 2020 Optimizing for the Future in Non-Stationary MDPs ICML 2020 Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020