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Evolution of spiking neural circuits in autonomous mobile robots
Author(s) -
Floreano Dario,
Epars Yann,
Zufferey JeanChristophe,
Mattiussi Claudio
Publication year - 2006
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20173
Subject(s) - computer science , spiking neural network , robot , encoding (memory) , mobile robot , electronic circuit , simple (philosophy) , encode , artificial intelligence , evolutionary robotics , microcontroller , evolvable hardware , evolutionary algorithm , artificial neural network , embedded system , engineering , biology , philosophy , biochemistry , epistemology , electrical engineering , gene
We describe evolution of spiking neural architectures to control navigation of autonomous mobile robots. Experimental results with simple fitness functions indicate that evolution can rapidly generate spiking circuits capable of navigating in textured environments with simple genetic representations that encode only the presence or absence of synaptic connections. Building on those results, we then describe a low‐level implementation of evolutionary spiking circuits in tiny microcontrollers that capitalizes on compact genetic encoding and digital aspects of spiking neurons. The implementation is validated on a sugar‐cube robot capable of developing functional spiking circuits for collision‐free navigation. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1005–1024, 2006.