1262 search results - page 45 / 253 » Reinforcement Learning: An Introduction |
TSMC
2008
13 years 7 months ago
2008
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
ICRA
2010
IEEE
13 years 6 months ago
2010
IEEE
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
GECCO
2009
Springer
14 years 17 days 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...
COLT
2000
Springer
14 years 9 days ago
2000
Springer
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process ( ¢¡¤£¦¥§ ), and focus on gradient ascent approache...