139 search results - page 4 / 28 » Model-based function approximation in reinforcement learning |
ICML
1996
IEEE
15 years 1 months ago
1996
IEEE
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
ICML
1995
IEEE
15 years 10 months ago
1995
IEEE
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
66
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AAMAS
2007
Springer
14 years 9 months ago
2007
Springer
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
105
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ATAL
2005
Springer
15 years 3 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
ICCBR
2005
Springer
15 years 3 months ago
2005
Springer
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...