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Todd Hester — most-cited papers & profile · Reinforcement Learning
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overview
Todd Hester
8
papers ·
1535
citations ·
24
h-index
Amazon (United States) · Google DeepMind (United Kingdom)
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Most-cited papers
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
2017 · 510 citations
Deep Q-learning from Demonstrations
2017 · 307 citations
Safe Exploration in Continuous Action Spaces
2018 · 276 citations
Challenges of Real-World Reinforcement Learning
2019 · 256 citations
Observe and Look Further: Achieving Consistent Performance on Atari
2018 · 87 citations
An empirical investigation of the challenges of real-world reinforcement learning
2020 · 52 citations
Robust Reinforcement Learning for Continuous Control with Model Misspecification
2019 · 38 citations
Adaptive Lambda Least-Squares Temporal Difference Learning
2016 · 9 citations
Top co-authors
Gabriel Dulac-Arnold
· 3
Olivier Pietquin
· 3
Bilal Piot
· 2
Cosmin Păduraru
· 2
Dan Horgan
· 2
Daniel J. Mankowitz
· 2
John Quan
· 2
Martin Riedmiller
· 2
Matej Vecerik
· 2
Nir Levine
· 2
Timothy Mann
· 2
Abbas Abdolmaleki
· 1
Topics
Exploration
Value-Based
Safe RL
Model-Based RL
Offline RL
Game AI
Policy Gradient