Hardware Evolution of Analog Circuits for In-situ Robotic Fault-Recovery
EH '05 Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware
Platform for Intrinsic Evolution of Analogue Neural Networks
RECONFIG '05 Proceedings of the 2005 International Conference on Reconfigurable Computing and FPGAs (ReConFig'05) on Reconfigurable Computing and FPGAs
Intrinsic Hardware Evolution of Neural Networks in Reconfigurable Analogue and Digital Devices
FCCM '06 Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
GRACE: generative robust analog circuit exploration
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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This paper details the hardware evolution of adaptive Spiking Neural Network (SNN) controllers, implemented on a network of cascaded Field Programmable Analogue Arrays (FPAAs). The fixed architecture, feed forward SNNs are trained using a Genetic Algorithm (GA). An obstacle avoidance simulated robotics controller application is chosen to test the FPAA reconfigurable hardware evolution platform. Evolved behaviours, resulting from FPAA-based SNN controllers, are compared with those obtained using software-based SNN implementations. Results presented indicate the emergence of effective behaviours and adaptation to environmental change.