65 search results - page 5 / 13 » Gradient Descent for General Reinforcement Learning |
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ICRA
2010
IEEE
14 years 8 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...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
NN
2002
Springer
14 years 9 months ago
2002
Springer
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
ECML
2007
Springer
15 years 3 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
KDD
2009
ACM
15 years 10 months ago
2009
ACM
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...