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Todd Hester
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2020 – today
- 2021
- [j5]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. 110(9): 2419-2468 (2021) - [c21]Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Velickovic:
ETA Prediction with Graph Neural Networks in Google Maps. CIKM 2021: 3767-3776 - [i11]Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Velickovic:
ETA Prediction with Graph Neural Networks in Google Maps. CoRR abs/2108.11482 (2021) - 2020
- [c20]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR 2020 - [i10]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
An empirical investigation of the challenges of real-world reinforcement learning. CoRR abs/2003.11881 (2020)
2010 – 2019
- 2019
- [c19]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. ICRA 2019: 754-760 - [i9]Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester:
Challenges of Real-World Reinforcement Learning. CoRR abs/1904.12901 (2019) - [i8]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/1906.07516 (2019) - 2018
- [c18]Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys:
Deep Q-learning From Demonstrations. AAAI 2018: 3223-3230 - [i7]Gal Dalal, Krishnamurthy Dvijotham, Matej Vecerík, Todd Hester, Cosmin Paduraru, Yuval Tassa:
Safe Exploration in Continuous Action Spaces. CoRR abs/1801.08757 (2018) - [i6]Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, Gabriel Barth-Maron, Hado van Hasselt, John Quan, Mel Vecerík, Matteo Hessel, Rémi Munos, Olivier Pietquin:
Observe and Look Further: Achieving Consistent Performance on Atari. CoRR abs/1805.11593 (2018) - [i5]Mel Vecerík, Oleg Sushkov, David Barker, Thomas Rothörl, Todd Hester, Jonathan Scholz:
A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning. CoRR abs/1810.01531 (2018) - 2017
- [j4]Todd Hester, Peter Stone:
Intrinsically motivated model learning for developing curious robots. Artif. Intell. 247: 170-186 (2017) - [i4]Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys:
Learning from Demonstrations for Real World Reinforcement Learning. CoRR abs/1704.03732 (2017) - [i3]Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller:
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR abs/1707.08817 (2017) - 2016
- [i2]Timothy A. Mann, Hugo Penedones, Shie Mannor, Todd Hester:
Adaptive Lambda Least-Squares Temporal Difference Learning. CoRR abs/1612.09465 (2016) - 2013
- [b1]Todd Hester:
TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains. Studies in Computational Intelligence 503, Springer 2013, ISBN 978-3-319-01167-7, pp. 1-147 - [j3]Todd Hester, Peter Stone:
TEXPLORE: real-time sample-efficient reinforcement learning for robots. Mach. Learn. 90(3): 385-429 (2013) - [c17]Todd Hester, Manuel Lopes, Peter Stone:
Learning exploration strategies in model-based reinforcement learning. AAMAS 2013: 1069-1076 - [c16]Todd Hester, Peter Stone:
The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots. RoboCup 2013: 536-543 - [c15]Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone:
The 2012 UT Austin Villa Code Release. RoboCup 2013: 552-559 - 2012
- [c14]Todd Hester, Peter Stone:
TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. AAAI Spring Symposium: Designing Intelligent Robots 2012 - [c13]Todd Hester, Peter Stone:
Intrinsically motivated model learning for a developing curious agent. ICDL-EPIROB 2012: 1-6 - [c12]Todd Hester, Michael J. Quinlan, Peter Stone:
RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for robot control. ICRA 2012: 85-90 - [c11]Samuel Barrett, Katie Long Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, Peter Stone:
UT Austin Villa 2012: Standard Platform League World Champions. RoboCup 2012: 36-47 - [p1]Todd Hester, Peter Stone:
Learning and Using Models. Reinforcement Learning 2012: 111-141 - 2011
- [i1]Todd Hester, Michael J. Quinlan, Peter Stone:
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control. CoRR abs/1105.1749 (2011) - 2010
- [j2]Shyamal Patel, Richard Hughes, Todd Hester, Joel Stein, Metin Akay, Jennifer G. Dy, Paolo Bonato:
A Novel Approach to Monitor Rehabilitation Outcomes in Stroke Survivors Using Wearable Technology. Proc. IEEE 98(3): 450-461 (2010) - [c10]Todd Hester, Peter Stone:
Real time targeted exploration in large domains. ICDL 2010: 191-196 - [c9]Todd Hester, Michael J. Quinlan, Peter Stone:
Generalized model learning for Reinforcement Learning on a humanoid robot. ICRA 2010: 2369-2374
2000 – 2009
- 2009
- [c8]Todd Hester, Peter Stone:
Generalized model learning for reinforcement learning in factored domains. AAMAS (2) 2009: 717-724 - [c7]Shivaram Kalyanakrishnan, Todd Hester, Michael J. Quinlan, Yinon Bentor, Peter Stone:
Three Humanoid Soccer Platforms: Comparison and Synthesis. RoboCup 2009: 140-152 - 2008
- [j1]Shyamal Patel, Todd Hester, Richard Hughes, Nancy Huggins, Alice Flaherty, David G. Standaert
, John Growdon, Paolo Bonato:
Processing Wearable Sensor Data to Optimize Deep-Brain Stimulation. IEEE Pervasive Comput. 7(1): 56-61 (2008) - [c6]Nicholas K. Jong, Todd Hester, Peter Stone:
The utility of temporal abstraction in reinforcement learning. AAMAS (1) 2008: 299-306 - [c5]Todd Hester, Peter Stone:
Negative information and line observations for Monte Carlo localization. ICRA 2008: 2764-2769 - 2006
- [c4]Todd Hester, Richard Hughes, Delsey M. Sherrill, Bethany Knorr, Metin Akay, Joel Stein, Paolo Bonato:
Using Wearable Sensors to Measure Motor Abilities following Stroke. BSN 2006: 5-8 - [c3]Shyamal Patel, Delsey M. Sherrill, Richard Hughes, Todd Hester, Theresa Lie-Nemeth, Paolo Bonato, David G. Standaert
Analysis of the Severity of Dyskinesia in Patients with Parkinson's Disease via Wearable Sensors. BSN 2006: 123-126 - [c2]Todd Hester, Delsey M. Sherrill, Paolo Bonato, Mathieu Hamel, Karine Perreault, Patrick Boissy:
Using Wearable Sensors to Analyze the Quality of Use of Mobility Assistive Devices. BSN 2006: 127-130 - [c1]Todd Hester, Delsey M. Sherrill, Mathieu Hamel, Karine Perreault, Patrick Boissy, Paolo Bonato:
Identification of Tasks Performed by Stroke Patients Using a Mobility Assistive Device. EMBC 2006: 1501-1504
Coauthor Index
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