FPGA implementation of spiking neural networks - an initial step towards building tangible collaborative autonomous agents
- Resource Type
- Conference
- Authors
- Bellis, S.; Razeeb, K.M.; Saha, C.; Delaney, K.; O'Mathuna, C.; Pounds-Cornish, A.; de Souza, G.; Colley, M.; Hagras, H.; Clarke, G.; Callaghan, V.; Argyropoulos, C.; Karistianos, C.; Nikiforidis, G.
- Source
- Proceedings. 2004 IEEE International Conference on Field- Programmable Technology (IEEE Cat. No.04EX921) Field-programmable technology Field-Programmable Technology, 2004. Proceedings. 2004 IEEE International Conference on. :449-452 2004
- Subject
- Components, Circuits, Devices and Systems
Field programmable gate arrays
Neural networks
Collaboration
Autonomous agents
Collaborative work
Service robots
Buildings
Multiagent systems
Fault detection
Humans
- Language
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.