Todd Hester

Deep Q-learning From Demonstrations

Todd Hester, Matej Vecerík, Olivier Pietquin et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2018 · 809 citations · Full text

Computing, Autonomous Systems, Computer Science +15

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz et al. · Machine Learning · 2021 · 570 citations · Full text

Computing, Computer Science, Artificial Intelligence +11

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Todd Hester, Jonathan Scholz, Fumin Wang et al. · arXiv (Cornell University) · 2017 · 510 citations · Full text

Engineering, Computer Science, Human-robot Interaction +16

Deep Q-learning from Demonstrations

Todd Hester, Matej Vecerík, Olivier Pietquin et al. · arXiv (Cornell University) · 2017 · 307 citations · Full text

Computing, Autonomous Systems, Computer Science +15

Safe Exploration in Continuous Action Spaces

Gal Dalal, Krishnamurthy Dvijotham, Matej Vecerík et al. · arXiv (Cornell University) · 2018 · 276 citations · Full text

Computing, Autonomous Systems, Computer Science +16