Design and deployment of Hybrid Intelligent Systems
Due to the hybrid nature of most real-life problems, both data and knowledge must be applied to find a proper solution. In keeping with this idea, hybrid intelligent systems combines different artificial intelligence techniques and paradigms (symbolic and sub-symbolic) to construct more robust and reliable problem solving models....
Hybrid Artificial Intelligent Systems (HAISs) proved to overcome previous proposals when dealing with real-life and complex problems. This new paradigm from the AI field enables the succesfull application of combined techniques and models to deal with complex problems. HAISs have been applied to many different problems, getting nice preformance results.
The research group has wide experience on the design, development and deployment of such intelligent systems, to solve practical problems from a range of different applications: parameter tuning of machine-tools, network security, knowledge management, etc.
It requires choosing the appropriate techniques (Artificial Neural Networks, machine learning models, evolutionary learning techniques, optimization mechanisms, etc) and combining them for each one of the problems, adjusting to the specific nature of the problem....
By the combination of different AI technologies, the limitations of individual models and paradigms are overcame.
Problems with a hybrid nature, whose solution requires the combination of different techniques....
Applied Computational Intelligence
Jose Manuel López López
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