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133
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ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 9 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
141
Voted
HICSS
2000
IEEE
134views Biometrics» more  HICSS 2000»
15 years 7 months ago
Peer-to-Peer Valuation as a Mechanism for Reinforcing Active Learning in Virtual Communities: Actualizing Social Exchange Theory
As knowledge becomes the primary focus of work in many industries, virtual communities and groups are emerging as part of new organizational forms. Within these virtual forms, eff...
Amrit Tiwana, Ashley A. Bush
AAAI
2008
15 years 5 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
108
Voted
NECO
2007
87views more  NECO 2007»
15 years 2 months ago
Reinforcement Learning State Estimator
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
Jun Morimoto, Kenji Doya
AAAI
2011
14 years 3 months ago
Value Function Approximation in Reinforcement Learning Using the Fourier Basis
We describe the Fourier Basis, a linear value function approximation scheme based on the Fourier Series. We empirically evaluate its properties, and demonstrate that it performs w...
George Konidaris, Sarah Osentoski, Philip Thomas