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AR
2008
188views more  AR 2008»
13 years 5 months ago
Intentional Control for Planetary Rover SRR
Intentional behavior is a basic property of intelligence and it incorporates the cyclic operation of prediction, testing by action, sensing, perceiving, and assimilating the exper...
Robert Kozma, Terry Huntsberger, Hrand Aghazarian,...
NN
2010
Springer
187views Neural Networks» more  NN 2010»
13 years 10 days ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
ICRA
2009
IEEE
227views Robotics» more  ICRA 2009»
14 years 7 days ago
Adaptive autonomous control using online value iteration with gaussian processes
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
Axel Rottmann, Wolfram Burgard
NN
2002
Springer
113views Neural Networks» more  NN 2002»
13 years 5 months ago
Control of exploitation-exploration meta-parameter in reinforcement learning
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Shin Ishii, Wako Yoshida, Junichiro Yoshimoto
ICANN
2010
Springer
13 years 6 months ago
Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...