Title :
Autonomous learning design in system-on-chip
Author :
Yimin Zhou ; Krundel, Ludovic ; Mulvaney, David ; Chouliaras, Vassilios ; Guoqing Xu ; Guoqiang Fu
Author_Institution :
Shenzhen Inst. of Adv. Technol., Shenzhen, China
Abstract :
The solving strategy of artificial intelligence (AI) is adopted with bottom-up design to solve its hard problems. To tackle end-to-end AI-hard problems, a highly self-adaptive control system-on-chip has been developed to self-learn its internal and external resources with the aid of sets of sensors and actuators. Inspired by biological cell learning theory, different approaches of modelling techniques have been derived together with machine learning methods to the embedded control systems so as to perform different tasks. Some experimental results have shown the developments.
Keywords :
cellular automata; learning (artificial intelligence); system-on-chip; actuators; artificial intelligence; autonomous learning design; biological cell learning theory; bottom-up design; embedded control systems; end-to-end AI-hard problems; machine learning methods; self-adaptive control system-on-chip; sensors; Artificial neural networks; Biological neural networks; Biological system modeling; Field programmable gate arrays; Hardware; Neurons; Robots;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on
Conference_Location :
Shenzhen
DOI :
10.1109/ROBIO.2013.6739603