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

S. Bellis, Kafil M. Razeeb, Chitta Saha, Kevin J. Delaney, Cian O’Mathúna, A. Pounds-Cornish, G. de Souza, Martin Colley, Hani Hagras, Graham S. Clarke, Vic Callaghan, Christos Argyropoulos, C. Karistianos, Georgios Nikiforidis

发表年份
2005
引用次数
32

摘要

This work contains the results of an initial study into the FPGA implementation 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/investigate 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 variety of applications where it is difficult 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 platform and results of a robotic wall following task are discussed by comparison with software driven robots and simulations.

关键词

Field-programmable gate arrayComputer scienceTask (project management)Variety (cybernetics)ExploitArtificial neural networkEmbedded systemRobotSpiking neural networkSoftware

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