12 search results - page 2 / 3 » Autonomous blimp control using model-free reinforcement lear... |
ICRA
2009
IEEE
13 years 11 months ago
2009
IEEE
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
CORR
2006
Springer
13 years 4 months ago
2006
Springer
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...
ICANNGA
2007
Springer
13 years 10 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
EUROCAST
2007
Springer
13 years 10 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
ICAC
2008
IEEE
13 years 11 months ago
2008
IEEE
—Large scale production grids are an important case for autonomic computing. They follow a mutualization paradigm: decision-making (human or automatic) is distributed and largely...