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» A novel method for learning policies from constrained motion
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CVGIP
2006
106views more  CVGIP 2006»
13 years 5 months ago
Precomputing avatar behavior from human motion data
Creating controllable, responsive avatars is an important problem in computer games and virtual environments. Recently, large collections of motion capture data have been exploite...
Jehee Lee, Kang Hoon Lee
ECAI
2006
Springer
13 years 9 months ago
Learning by Automatic Option Discovery from Conditionally Terminating Sequences
Abstract. This paper proposes a novel approach to discover options in the form of conditionally terminating sequences, and shows how they can be integrated into reinforcement learn...
Sertan Girgin, Faruk Polat, Reda Alhajj
ECML
2005
Springer
13 years 11 months ago
Model-Based Online Learning of POMDPs
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony
TOG
2002
98views more  TOG 2002»
13 years 5 months ago
Synthesis of complex dynamic character motion from simple animations
In this paper we present a general method for rapid prototyping of realistic character motion. We solve for the natural motion from a simple animation provided by the animator. Ou...
C. Karen Liu, Zoran Popovic
NIPS
2008
13 years 7 months ago
Policy Search for Motor Primitives in Robotics
Many motor skills in humanoid robotics can be learned using parametrized motor primitives as done in imitation learning. However, most interesting motor learning problems are high...
Jens Kober, Jan Peters