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» Variational methods for Reinforcement Learning
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AUSAI
1999
Springer
14 years 3 days ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
IWEC
2007
13 years 9 months ago
Pass the Ball: Game-Based Learning of Software Design
Based on our experience using active learning methods to teach object-oriented software design we propose a game-based approach to take the classroom experience into a virtual envi...
Guillermo Jiménez-Díaz, Mercedes G&o...
IROS
2006
IEEE
100views Robotics» more  IROS 2006»
14 years 1 months ago
Gait Generation for Passive Running via Iterative Learning Control
Abstract— This paper proposes a novel framework to generate optimal passive gait trajectories for a planar one-legged hopping robot via iterative learning control. The proposed m...
Satoshi Satoh, Kenji Fujimoto, Sang-Ho Hyon
ICPR
2000
IEEE
14 years 6 days ago
Handwritten Character Segmentation Using Transformation-Based Learning
This paper presents a character segmentation algorithm for unconstrained cursive handwritten text. The transformation-based learning method and a simplified variation of it are us...
Ergina Kavallieratou, Efstathios Stamatatos, Nikos...
SIGGRAPH
2010
ACM
14 years 9 days ago
Gesture controllers
We introduce gesture controllers, a method for animating the body language of avatars engaged in live spoken conversation. A gesture controller is an optimal-policy controller tha...
Sergey Levine, Philipp Krähenbühl, Sebastian Thr...