DocumentCode
2919223
Title
Towards the evolution of an artificial homeostatic system
Author
Moioli, Renan C. ; Vargas, Patricia A. ; Von Zuben, Fernando J. ; Husbands, Phil
Author_Institution
Sch. of Electr. & Comput. Eng., Lab. of Bioinf. Bio-Inspired Comput., Unicamp, Campinas
fYear
2008
fDate
1-6 June 2008
Firstpage
4023
Lastpage
4030
Abstract
This paper presents an artificial homeostatic system (AHS) devoted to the autonomous navigation of mobile robots, with emphasis on neuro-endocrine interactions. The AHS is composed of two modules, each one associated with a particular reactive task and both implemented using an extended version of the GasNet neural model, denoted spatially unconstrained GasNet model or simply non-spatial GasNet (NSGasNet). There is a coordination system, which is responsible for the specific role of each NSGasNet at a given operational condition. The switching among the NSGasNets is implemented as an artificial endocrine system (AES), which is based on a system of coupled nonlinear difference equations. The NSGasNets are synthesized by means of an evolutionary algorithm. The obtained neuro-endocrine controller is adopted in simulated and real benchmark applications, and the additional flexibility provided by the use of NSGasNet, together with the existence of an automatic coordination system, guides to convincing levels of performance.
Keywords
difference equations; evolutionary computation; mobile robots; nonlinear equations; path planning; GasNet neural model; artificial endocrine system; artificial homeostatic system; automatic coordination system; autonomous navigation; coupled nonlinear difference equations; evolutionary algorithm; mobile robots; neuro-endocrine controller; neuro-endocrine interactions; unconstrained GasNet model; Artificial neural networks; Automated highways; Biological system modeling; Biology computing; Computational modeling; Control system synthesis; Endocrine system; Evolution (biology); Mobile robots; Plastics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631346
Filename
4631346
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