164 search results - page 11 / 33 » Self-Optimizing Memory Controllers: A Reinforcement Learning... |
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
NN
2007
Springer
13 years 7 months ago
2007
Springer
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
CIIA
2009
13 years 8 months ago
2009
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
GLOBECOM
2010
IEEE
13 years 5 months ago
2010
IEEE
Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...