5 search results - page 1 / 1 » Control Double Inverted Pendulum by Reinforcement Learning w... |
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
ICML
2009
IEEE
14 years 6 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...
ICML
2000
IEEE
14 years 6 months ago
2000
IEEE
We explore combining reinforcement learning with a hand-crafted local controller in a manner suggested by the chaotic control algorithm of Vincent, Schmitt and Vincent (1994). A c...
EVOW
2003
Springer
13 years 11 months ago
2003
Springer
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
GECCO
2004
Springer
13 years 11 months ago
2004
Springer
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...