56 search results - page 2 / 12 » Q-Learning in Continuous State and Action Spaces |
NIPS
2007
13 years 6 months ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
WSC
2000
13 years 6 months ago
2000
Many artificial intelligence techniques rely on the notion ate" as an abstraction of the actual state of the nd an "operator" as an abstraction of the actions that ...
AAAI
1998
13 years 6 months ago
1998
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
ICMLA
2004
13 years 6 months ago
2004
We present JoSTLe, an algorithm that performs value iteration on control problems with continuous actions, allowing this useful reinforcement learning technique to be applied to p...
ICML
2009
IEEE
14 years 5 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...