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ROBOCUP
2000
Springer
130views Robotics» more  ROBOCUP 2000»
13 years 7 months ago
Improvement Continuous Valued Q-learning and Its Application to Vision Guided Behavior Acquisition
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
Yasutake Takahashi, Masanori Takeda, Minoru Asada
ICRA
2007
IEEE
147views Robotics» more  ICRA 2007»
13 years 10 months ago
Neural Reinforcement Learning Controllers for a Real Robot Application
— Accurate and fast control of wheel speeds in the presence of noise and nonlinearities is one of the crucial requirements for building fast mobile robots, as they are required i...
Roland Hafner, Martin Riedmiller
ICRA
2005
IEEE
140views Robotics» more  ICRA 2005»
13 years 10 months ago
Fast Reinforcement Learning for Vision-guided Mobile Robots
— This paper presents a new reinforcement learning algorithm for accelerating acquisition of new skills by real mobile robots, without requiring simulation. It speeds up Q-learni...
Tomás Martínez-Marín, Tom Duc...
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
13 years 10 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...
CORR
2006
Springer
101views Education» more  CORR 2006»
13 years 4 months ago
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...