A Hybrid Intelligent Autonomous Model Developed Using Multi-Agent Systems
Anusua Ghosh, Andrew Nafalski, and Jeffery W Tweedale
University of South Australia/School of Electrical and Information Engineering, Adelaide, Australia
Abstract—Complex problem solving and decision making requires integrating two or more intelligent techniques as no algorithm or technique are sufficient to completely solve a problem. The systems developed by integrating different hard computing and soft computing techniques to solve problem are called Hybrid Systems. This paper presents the design, development and implementation of a hybrid intelligent autonomous model. The model is developed in phases, which comprises of different individual agents. This model will be used to analyse workstress related data in real time.
Index Terms—agent, multi-agent, artificial intelligence, hybrid system, neural networks
Cite: Anusua Ghosh, Andrew Nafalski, and Jeffery W Tweedale "A Hybrid Intelligent Autonomous Model Developed Using Multi-Agent Systems," International Journal of Electronics and Electrical Engineering, Vol. 1, No. 1, pp. 57-60, March 2013. doi: 10.12720/ijeee.1.1.57-60
Index Terms—agent, multi-agent, artificial intelligence, hybrid system, neural networks
Cite: Anusua Ghosh, Andrew Nafalski, and Jeffery W Tweedale "A Hybrid Intelligent Autonomous Model Developed Using Multi-Agent Systems," International Journal of Electronics and Electrical Engineering, Vol. 1, No. 1, pp. 57-60, March 2013. doi: 10.12720/ijeee.1.1.57-60
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