Risk Averse Reinforcement Learning Professors in Global

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Florian Shkurti
University of Toronto Canada
reinforcement learning
inverse reinforcement learning
imitation learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
reinforcement learning
deep reinforcement learning
robot learning
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Matthias Bickel
ETH Zurich Switzerland
reinforcement learning
inverse reinforcement learning
inverse optimization
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Yinbei Li
Singapore Institute of Technology Singapore
reinforcement learning
robot learning
imitation learning
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Muhammad Hafez
University of Southampton United Kingdom
reinforcement learning
robot learning
continual robot learning
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Giorgia Ramponi
University of Zurich Switzerland
reinforcement learning
imitation learning
multi-agent learning
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Yuhong Guo
Carleton University Canada
reinforcement learning
self-supervised learning
representation learning
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Rudolf Lioutikov
University of Texas at Austin United States of America
reinforcement learning
imitation learning
life-long active learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
rate learning
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Tommaso Palermo
London School of Economics United Kingdom
risk performance management
risk management
risk regulation
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Antoine Van Den Beemt
Eindhoven University of Technology Belgium
learning analytics
networked learning
challenge-based learning
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Silun Zhang
KTH Royal Institute of Technology Sweden
risk-averse reinforcement learning
safe reinforcement learning
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Colin Bellinger
University of Ottawa Canada
reinforcement learning
safe reinforcement learning
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Aditya Mahajan
McGill University Canada
reinforcement learning
multi-agent reinforcement learning
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Yuhua Zhu
University of California Los Angeles United States of America
reinforcement learning
continuous-time reinforcement learning
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Wendelin Böhmer
Delft University of Technology Netherlands
reinforcement learning
multi-agent reinforcement learning
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Rika Antonova
University of Cambridge United Kingdom
reinforcement learning
data-efficient reinforcement learning
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Morteza Haghir Chehreghani
University of Gothenburg Sweden
diversity-aware reinforcement learning
deep reinforcement learning
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Kurt Driessens
Maastricht University Netherlands
reinforcement learning
relational learning
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Kurt Driessens
Maastricht University Netherlands
reinforcement learning
relational learning
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Rupam Mahmood
University of Alberta Canada
reinforcement learning
real-time learning systems
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