Evolutionary fuzzy system for architecture control in a constructive neural network

Calvo, R.; Figueiredo, M.; Antonelo, Eric Aislan

doi:10.1109/CIRA.2005.1554333

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Evolutionary fuzzy system for architecture control in a constructive neural network

Calvo, R.; Figueiredo, M.; Antonelo, Eric Aislan

2005 • In 2005 International Symposium on Computational Intelligence in Robotics and Automation

Peer reviewed

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https://hdl.handle.net/10993/36485

DOI
10.1109/CIRA.2005.1554333

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Keywords :

mobile robots; fuzzy neural nets; evolutionary computation; navigation;evolutionary fuzzy system;architecture control;constructive neural network;autonomous navigation;classifier system;Takagi-Sugeno fuzzy rules;mobile robot;evolutionary learning;classifier fuzzy system;classifier systems;robot navigation;Fuzzy systems;Control systems;Neural networks;Navigation;Takagi-Sugeno model;Fuzzy control;Fuzzy neural networks;Mobile robots;Learning systems;Neurons;constructive neural networks;classifier systems;robot navigation

Abstract :

[en] This work describes an evolutionary system to control the growth of a constructive neural network for autonomous navigation. A classifier system generates Takagi-Sugeno fuzzy rules and controls the architecture of a constructive neural network. The performance of the mobile robot guides the evolutionary learning mechanism. Experiments show the efficiency of the classifier fuzzy system for analyzing if it is worth inserting a new neuron into the architecture.

Disciplines :

Computer science

Author, co-author :

Calvo, R.

Figueiredo, M.

Antonelo, Eric Aislan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)

External co-authors :

yes

Language :

English

Title :

Evolutionary fuzzy system for architecture control in a constructive neural network

Publication date :

2005

Event name :

International Symposium on Computational Intelligence in Robotics and Automation

Event date :

27-06-2005 to 30-06-2005

Audience :

International

Main work title :

2005 International Symposium on Computational Intelligence in Robotics and Automation

Publisher :

IEEE

Pages :

541-546

Peer reviewed :

Peer reviewed

Additional URL :

https://ieeexplore.ieee.org/abstract/document/1554333/

Available on ORBilu :

since 29 August 2018

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Bibliography

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