Sciweavers

NIPS
2008
13 years 6 months ago
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
John W. Roberts, Russ Tedrake
EWRL
2008
13 years 6 months ago
Policy Learning - A Unified Perspective with Applications in Robotics
Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper,...
Jan Peters, Jens Kober, Duy Nguyen-Tuong
ICML
2003
IEEE
14 years 5 months ago
Hierarchical Policy Gradient Algorithms
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
Mohammad Ghavamzadeh, Sridhar Mahadevan