DocumentCode
1637087
Title
Evolving modular genetic regulatory networks
Author
Bongard, Josh
Author_Institution
Artificial Intelligence Lab., Zurich Univ., Switzerland
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1872
Lastpage
1877
Abstract
We introduce a system that combines ontogenetic development and artificial evolution to automatically design robots in a physics-based, virtual environment. Through lesion experiments on the evolved agents, we demonstrate that the evolved genetic regulatory networks from successful evolutionary runs are more modular than those obtained from unsuccessful runs
Keywords
genetic algorithms; neural nets; robots; artificial evolution; evolved agents; evolving modular genetic regulatory networks; experiments; neural network; ontogenetic development; physics-based virtual environment; robot design; Bioinformatics; Biological information theory; Encoding; Evolution (biology); Genetics; Genomics; Robots; Shape; Testing; Virtual environment;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7282-4
Type
conf
DOI
10.1109/CEC.2002.1004528
Filename
1004528
Link To Document