373 search results - page 8 / 75 » Covariant Policy Search |
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Decentralized MDPs provide powerful models of interactions in multi-agent environments, but are often very difficult or even computationally infeasible to solve optimally. Here we...
NIPS
2008
13 years 9 months ago
2008
Many motor skills in humanoid robotics can be learned using parametrized motor primitives as done in imitation learning. However, most interesting motor learning problems are high...