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NIPS
2007
13 years 9 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
INFOCOM
1995
IEEE
13 years 11 months ago
Complexity of Gradient Projection Method for Optimal Routing in Data Networks
—In this paper, we derive a time-complexity bound for the gradient projection method for optimal routing in data networks. This result shows that the gradient projection algorith...
Wei Kang Tsai, John K. Antonio, Garng M. Huang
DATE
2008
IEEE
99views Hardware» more  DATE 2008»
14 years 2 months ago
Thermal Balancing Policy for Streaming Computing on Multiprocessor Architectures
As feature sizes decrease, power dissipation and heat generation density exponentially increase. Thus, temperature gradients in Multiprocessor Systems on Chip (MPSoCs) can serious...
Fabrizio Mulas, Michele Pittau, Marco Buttu, Salva...
ICANNGA
2007
Springer
105views Algorithms» more  ICANNGA 2007»
14 years 1 months ago
Reinforcement Learning in Fine Time Discretization
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...
Pawel Wawrzynski
NIPS
1998
13 years 9 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore