1799 search results - page 195 / 360 » Filtered Reinforcement Learning |
167
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NIPS
1992
15 years 5 months ago
1992
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
144
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AAMAS
2002
Springer
15 years 4 months ago
2002
Springer
Abstract. One of the main questions concerning learning in a Multi-Agent System's environment is: "(How) can agents benefit from mutual interaction during the learning pr...
148
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CORR
2010
Springer
15 years 4 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
114
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NIPS
2000
15 years 5 months ago
2000
Explaining away has mostly been considered in terms of inference of states in belief networks. We show how it can also arise in a Bayesian context in inference about the weights g...
164
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EUSFLAT
2009
15 years 2 months ago
2009
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...