inverse reinforcement learning

Adversarial Imitation via Variational Inverse Reinforcement Learning ICLR 2019 Asking Easy Questions: A User-Friendly Approach to Active Reward Learning CoRL 2019 Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations CoRL 2019 Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning AAAI 2019 Exploring Computational User Models for Agent Policy Summarization IJCAI 2019 Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations ICML 2019 From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following ICLR 2019 Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog EMNLP 2019 Inferring Task Goals and Constraints using Bayesian Nonparametric Inverse Reinforcement Learning CoRL 2019 Interactive Teaching Algorithms for Inverse Reinforcement Learning IJCAI 2019 IRLAS: Inverse Reinforcement Learning for Architecture Search CVPR 2019 Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games AAAI 2019 Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints NeurIPS 2019 Learning a Prior over Intent via Meta-Inverse Reinforcement Learning ICML 2019 Learning from a Learner ICML 2019 Learning Reward Functions by Integrating Human Demonstrations and Preferences RSS 2019 Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications AAAI 2019 Meta-Inverse Reinforcement Learning with Probabilistic Context Variables NeurIPS 2019 Model-Free IRL Using Maximum Likelihood Estimation AAAI 2019 Multi-Agent Adversarial Inverse Reinforcement Learning ICML 2019 Non-Cooperative Inverse Reinforcement Learning NeurIPS 2019 On the Correctness and Sample Complexity of Inverse Reinforcement Learning NeurIPS 2019 On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference ICML 2019 Preferences Implicit in the State of the World ICLR 2019 SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies NeurIPS 2019