1262 search results - page 172 / 253 » Reinforcement Learning: An Introduction |
ML
2002
ACM
13 years 8 months ago
2002
ACM
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
SMC
2007
IEEE
14 years 2 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
IROS
2006
IEEE
14 years 2 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...
ECML
2005
Springer
14 years 1 months ago
2005
Springer
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
ATAL
2008
Springer
13 years 10 months ago
2008
Springer
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...