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AAAI
2000
13 years 10 months ago
Interactive Training for Synthetic Characters
Compelling synthetic characters must behave in ways that reflect their past experience and thus allow for individual personalization. We therefore need a method that allows charac...
Song-Yee Yoon, Robert C. Burke, Bruce Blumberg, Ge...
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
14 years 2 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...
TSMC
2008
84views more  TSMC 2008»
13 years 8 months ago
Learning Inverse Kinematics: Reduced Sampling Through Decomposition Into Virtual Robots
We propose a technique to speedup the learning of the inverse kinematics of a robot manipulator by decomposing it into two or more virtual robot arms. Unlike previous decomposition...
Vicente Ruiz de Angulo, Carme Torras
ICRA
2010
IEEE
186views Robotics» more  ICRA 2010»
13 years 6 months ago
Multi-class batch-mode active learning for image classification
Accurate image classification is crucial in many robotics and surveillance applications
Ajay J. Joshi, Fatih Porikli, Nikolaos Papanikolop...
COLT
1991
Springer
14 years 4 days ago
The Role of Learning in Autonomous Robots
Applications of learning to autonomous agents (simulated or real) have often been restricted to learning a mapping from perceived state of the world to the next action to take. Of...
Rodney A. Brooks