65 search results - page 7 / 13 » Gradient Descent for General Reinforcement Learning |
109
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GECCO
2009
Springer
14 years 7 months ago
2009
Springer
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
110
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IWLCS
2005
Springer
15 years 3 months ago
2005
Springer
Aiming to clarify the convergence or divergence conditions for Learning Classifier System (LCS), this paper explores: (1) an extreme condition where the reinforcement process of ...
CORR
2011
Springer
14 years 1 months ago
2011
Springer
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
CORR
2002
Springer
14 years 9 months ago
2002
Springer
We present a generalization of conventional artificial neural networks that allows for a functional equivalence to multi-expert systems. The new model provides an architectural fr...