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133
Voted
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 10 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...
116
Voted
CIMCA
2008
IEEE
15 years 10 months ago
Adaption of Courses and Learning Environment to the User Context in dotLRN
The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features ...
David Huerva, Jeimy Velez, Silvia Baldiris, Ram&oa...
142
Voted
KR
1992
Springer
15 years 7 months ago
Learning Useful Horn Approximations
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
Russell Greiner, Dale Schuurmans
121
Voted
AR
2002
157views more  AR 2002»
15 years 3 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.
138
Voted
ATAL
2007
Springer
15 years 9 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone