Policy Learning

MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks IJCAI 2021 Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning EMNLP 2021 Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning AAAI 2021 MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration ICML 2021 Meta-Model-Based Meta-Policy Optimization ACML 2021 Meta-Reinforcement Learning by Tracking Task Non-stationarity IJCAI 2021 Meta-Reinforcement Learning for Mastering Multiple Skills and Generalizing across Environments in Text-based Games ACL 2021 Minimax Model Learning AISTATS 2021 MobILE: Model-Based Imitation Learning From Observation Alone NeurIPS 2021 Model-Based Episodic Memory Induces Dynamic Hybrid Controls NeurIPS 2021 Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts IJCAI 2021 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling ICML 2021 Muesli: Combining Improvements in Policy Optimization ICML 2021 Multi-Objective Reinforcement Learning for Designing Ethical Environments IJCAI 2021 Multi-task Actor-Critic with Knowledge Transfer via a Shared Critic ACML 2021 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021 Navigating to the Best Policy in Markov Decision Processes NeurIPS 2021 Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes COLT 2021 Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs ICML 2021 Near Optimal Policy Optimization via REPS NeurIPS 2021 Near Optimal Reward-Free Reinforcement Learning ICML 2021 Neural optimal feedback control with local learning rules NeurIPS 2021 Neuro-Symbolic Approaches for Text-Based Policy Learning EMNLP 2021 Offline Model-based Adaptable Policy Learning NeurIPS 2021 Offline RL Without Off-Policy Evaluation NeurIPS 2021