128 search results - page 12 / 26 » Hierarchically Optimal Average Reward Reinforcement Learning |
NIPS
2008
13 years 9 months ago
2008
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
NECO
2007
13 years 7 months ago
2007
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
NN
2002
Springer
13 years 7 months ago
2002
Springer
Anatomical and pharmacological evidence suggests that the dorsal raphe serotonin system and the ventral tegmental and substantia nigra dopamine system may act as mutual opponents....
ICRA
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
ATAL
2006
Springer
13 years 11 months ago
2006
Springer
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...