9 search results - page 1 / 2 » Feature selection and policy optimization for distributed in... |
IEEEPACT
2008
IEEE
13 years 11 months ago
2008
IEEE
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of 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...
GECCO
2009
Springer
13 years 9 months ago
2009
Springer
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
FLAIRS
2004
13 years 6 months ago
2004
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...