Automatic generation of fuzzy neural networks via reinforcement learning with applications in path planning of mobile robots

Automatic generation of fuzzy neural networks via reinforcement learning with applications in path planning of mobile robots

In this thesis, a novel Reinforcement Learning (RL) methodology, termed Dynamic Self-Generated Fuzzy Q-Learning (DSGFQL) is developed for generating Fuzzy Neural Networks (FNNs). In the DSGFQL system, RL is adopted for both structure identification and parameters estimation of FNNs. Structure...

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Bibliographic Details
Main Author: Zhou, Yi
Other Authors: Er, Meng Joo
Format: Thesis
Language:English
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:https://hdl.handle.net/10356/13267

Internet

https://hdl.handle.net/10356/13267

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