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International Conference on Mechanical Engineering and Technology (ICMET-London 2011)

Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011

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.

Abstract
Keywords
Introduction
Hardware Digital Neural Tissue Model
Cellular Autonomous Rule
Experiment Results and Analysis
Conculsions and Future Works
Acknowledgment
References
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