Multi Robot Learning Adaptation Professors in Global

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Gerard Gorman
Imperial College London United Kingdom
multi-physics modeling
adaptive computational algorithms
multi-scale modeling
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Howard Schwartz
Carleton University Canada
multi robot learning adaptation
adaptive learning systems
cooperative control of multiple autonomous robots
adaptive control
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Sacha Morris
King's College London United Kingdom
learning-based approaches for adaptive robotic behavior
adaptive variable impedance control of robotic systems
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Nicki Mitchell
University of Western Australia Australia
climate change adaptation
adaptive management
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
robot learning
co-adaptation
reinforcement learning
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Martina Caretta
Lund University Sweden
climate change adaptation
agricultural adaptation
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Michael Bowling
University of Alberta Canada
multiagent learning
reinforcement learning
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Chi Jin
Princeton University United States of America
multiagent learning
reinforcement learning
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Peter Stone
University of Texas at Austin United States of America
multiagent learning
reinforcement learning
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Michael Bowling
University of Alberta Canada
multiagent learning
reinforcement learning
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Clark Lab
University of Pittsburgh United States of America
evolutionary adaptation
adaptive evolution
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James Hubbard
Texas A&M University United States of America
human-robot teaming
smart adaptive structures
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Guowei Ma
University of Western Australia Australia
multi-physics modelling
multi-scale modelling
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Akke Suiker
Eindhoven University of Technology Belgium
multi-physics modeling
multi-scale modeling
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Yung Shin
Purdue University United States of America
multi-physics modeling
multi-scale modeling
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Maryam Fazel
University of Washington United States of America
reinforcement learning
learning control
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Hadas Kress-gazit
Cornell University Netherlands
human robot interaction
modular robots
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Hadas Kress-gazit
Cornell University Netherlands
human robot interaction
modular robots
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Gui Liberali
Erasmus University Rotterdam Netherlands
reinforcement learning
adaptive experiments
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Maryam Kamgarpour
École Polytechnique Fédérale de Lausanne Switzerland
reinforcement learning
multi-agent decision-making
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Cesare Alippi
Università della Svizzera italiana Switzerland
adaptation learning
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