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This paper contains the results of an initial study into the FPGA implementotion of a spiking neural network. This work was undertaken as a task in a project that aims to design and develop a new kind of tangible Collaborative Autonomous Agent. The project intends to exploit/invesrigate methods for engineering emergent collective behaviour in large societies of actual miniature agents that can learn and evolve. Such multi-agent systems could be used to detect and collectively repair faults in a vane@ of applications where it is dijficult for humans to gain access, such as fluidic environments found in critical components of material/industrial systems. The initial achievement of implementation of a spiking neural network on a FPGA hardware plaform and results of a robotic wall following task are discussed by comparison with sofnvare driven robots and simulations.

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Cited by 9 publications

References 44 publications

Unsupervised Learning and Self-Organization in Networks of Spiking Neurons

Unsupervised Learning and Self-Organization in Networks of Spiking Neurons

Modeling spiking neural networks

FPGA implementation of spiking neural networks - an initial step towards building tangible collaborative autonomous agents

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