reinforcement learning

Learning to Move with Affordance Maps ICLR 2020 Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems AAAI 2020 Learning to Score Behaviors for Guided Policy Optimization ICML 2020 Learning to solve the credit assignment problem ICLR 2020 Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation EMNLP 2020 Learning to summarize with human feedback NeurIPS 2020 Learning When and Where to Zoom With Deep Reinforcement Learning CVPR 2020 Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020 Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning NeurIPS 2020 Leveraging Discourse Rewards for Document-Level Neural Machine Translation COLING 2020 Leveraging Procedural Generation to Benchmark Reinforcement Learning ICML 2020 Lifelong Learning with a Changing Action Set AAAI 2020 Lookahead-Bounded Q-learning ICML 2020 Loss Function Search for Face Recognition ICML 2020 Lyceum: An efficient and scalable ecosystem for robot learning L4DC 2020 Making Efficient Use of Demonstrations to Solve Hard Exploration Problems ICLR 2020 MAPS: Multi-Agent reinforcement learning-based Portfolio management System. IJCAI 2020 Maxmin Q-learning: Controlling the Estimation Bias of Q-learning ICLR 2020 Measuring the Reliability of Reinforcement Learning Algorithms ICLR 2020 Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards AAAI 2020 Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards NeurIPS 2020 Meta-learning curiosity algorithms ICLR 2020 Meta-Learning through Hebbian Plasticity in Random Networks NeurIPS 2020 Meta-Learning with Warped Gradient Descent ICLR 2020 Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations AAAI 2020