125 search results - page 11 / 25 » Reinforcement Learning in Continuous Time and Space |
ICML
2003
IEEE
14 years 9 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
EVOW
2003
Springer
14 years 1 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 ...
ICRA
2010
IEEE
13 years 7 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...
ICES
2003
Springer
14 years 1 months ago
2003
Springer
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
PRIMA
2009
Springer
14 years 3 months ago
2009
Springer
In this article, we propose a method to adapt stepsize parameters used in reinforcement learning for dynamic environments. In general reinforcement learning situations, a stepsize...