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Policy Learning

2068 directly classified papers

Papers per year

Papers

Safe Policy Learning for Continuous Control CORL 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020
Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation CORL 2020
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning NIPS 2020
Preference-based Reinforcement Learning with Finite-Time Guarantees NIPS 2020
R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making NIPS 2020
Constrained Reinforcement Learning via Policy Splitting ACML 2020
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs AAAI 2020
Discretizing Continuous Action Space for On-Policy Optimization AAAI 2020
Attentive Experience Replay AAAI 2020
Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving CVPR 2020
How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy Optimization NIPS 2020
Learning Guidance Rewards with Trajectory-space Smoothing NIPS 2020
Discovering Reinforcement Learning Algorithms NIPS 2020
Experimental design for MRI by greedy policy search NIPS 2020
Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward UAI 2020
No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020
GraphOpt: Learning Optimization Models of Graph Formation ICML 2020
Safe Reinforcement Learning in Constrained Markov Decision Processes ICML 2020
Learning to search efficiently for causally near-optimal treatments NIPS 2020
Forethought and Hindsight in Credit Assignment NIPS 2020
Inverse Reinforcement Learning from a Gradient-based Learner NIPS 2020
Guided Dialogue Policy Learning without Adversarial Learning in the Loop EMNLP 2020
Incorporating Stylistic Lexical Preferences in Generative Language Models EMNLP 2020
Modeling Protagonist Emotions for Emotion-Aware Storytelling EMNLP 2020