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TSMC
2008
177views more  TSMC 2008»
14 years 10 months ago
Adaptive Critic Learning Techniques for Engine Torque and Air-Fuel Ratio Control
A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning con...
Derong Liu, Hossein Javaherian, Olesia Kovalenko, ...
ICML
2009
IEEE
16 years 15 days ago
K-means in space: a radiation sensitivity evaluation
Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environment...
Kiri L. Wagstaff, Benjamin Bornstein
CBMS
2006
IEEE
15 years 5 months ago
Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia
The growing availability of high throughput measurement devices in the operating room makes possible the collection of a huge amount of data about the state of the patient and the...
Olivier Caelen, Gianluca Bontempi, Eddy Coussaert,...
ECML
2006
Springer
15 years 3 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
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 ...
Scott Proper, Prasad Tadepalli
TSMC
2002
105views more  TSMC 2002»
14 years 11 months ago
On the use of learning automata in the control of broadcast networks: a methodology
Due to its fixed assignment nature, the well-known time division multiple access (TDMA) protocol suffers from poor performance when the offered traffic is bursty. In this paper, an...
Georgios I. Papadimitriou, Mohammad S. Obaidat, An...