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115
Voted
FLAIRS
2003
15 years 5 months ago
2003
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
114
Voted
ATAL
2010
Springer
15 years 4 months ago
2010
Springer
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...
126
Voted
IJON
2006
15 years 3 months ago
2006
In this work, we propose a variation of a direct reinforcement learning algorithm, suitable for usage with spiking neurons based on the spike response model (SRM). The SRM is a bi...
147
Voted
ATAL
2007
Springer
15 years 10 months ago
2007
Springer
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
142
Voted
ICML
2001
IEEE
16 years 4 months ago
2001
IEEE
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...