Optimize Expert Knowledge Acquisition with Attribute Calculation: How to Understand Twin Turing Machine

This article aims to introduce how to use the attribute calculation method to achieve the purpose of optimization expert knowledge acquisition through several typical examples. The method is as follows: Firstly, the cognitive system framework in the expert’s mind is transformed into the information processing mode of the computer through a typical attribute coordinate; further, through a set of typical attribute calculations, the artificial knowledge ontology can be transformed into a computer for the software model is repetitively reused; finally, the weight of the expert’s mind is transformed into a software-simulated gravity judgment by a typical geometric algebraic method and geometric product, and then statistical analysis can be performed. The result: not only the property theory and its computer modeling and simulation can be realized, but also the expert knowledge acquisition from the unattainable or inscrutable altar to the classrooms and campuses of teachers and students, as that become a routine that you can operate or enjoy at any time. The significance lies in: the small-scale production of knowledge mode that lasts for thousands of years, and the attribute calculation method to optimize the human-computer collaboration and synergy paradigm of expert knowledge acquisition, which is transformed into a large-scale production of knowledge mode in daily teaching activities with teachers and students. This parallel production of cognitive systems and information processing is not only operational, but also an optimal simplification of knowledge center construction.

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