| Bibliography | Oubbati, Mohamed; Levi, Paul; Schanz, Michael: Meta-learning for Adaptive Identification of Non-linear Dynamical Systems..
In: Proceedings of the Joint 20th IEEE International Symposium on Intelligent Control & 13th Mediterranean Conference on Control and Automation (2005 ISIC-MED)..
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 473-478, english.
Limassol, Cyprus: IEEE, June 27, 2005.
Article in Proceedings (Conference Paper).
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| Corporation | IEEE |
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| CR-Schema | I.2.8 (Problem Solving, Control Methods, and Search)
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| Keywords | Adaptive Identification; RNNs; Non-linear Dynamical Systems; Meta-learning. |
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| Abstract | Adaptive Identification of Non-linear Dynamical Systems via Recurrent Neural Networks (RNNs) is presented in this paper. We explore the notion that a fixed-weight RNN needs to change only its internal state to change its behavior policy. This ability is acquired through prior training procedure that enable the learning of adaptive behaviors. Some simulation results are presented.
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| Contact | Mohamed.Oubbati@informatik.uni-stuttgart.de |
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| Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Image Understanding
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| Project(s) | SFB-627
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| Entry date | July 30, 2005 |
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