International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
107 Spiking Neural Networks on Self-Updating System-on-Chip for Autonomous Control
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The artificial intelligence (AI) technique has suffered in solving its computationally hard problems in recent years. In this paper, a self-upgrading autonomous system is designed to tackle end-to-end AI-hard problems and to achieve self-adapting communication via modular and hierarchical extension from linguistic and semiotic constructs. A system-on-a-chip (SoC) self-adaptive control system can learn arbitrary shape of the robot body or machine parts. Simulation results have proved the effectiveness of learning abilities of the proposed autonomous system.