91 search results - page 6 / 19 » Parameter-exploring policy gradients |
ECML
2007
Springer
14 years 1 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
IROS
2006
IEEE
14 years 1 months ago
2006
IEEE
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
ICANN
2010
Springer
13 years 8 months ago
2010
Springer
So-called Physical Unclonable Functions are an emerging, new cryptographic and security primitive. They can potentially replace secret binary keys in vulnerable hardware systems an...
NIPS
2008
13 years 9 months ago
2008
Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the bel...