Training in Research on Cognitive Control Systems
In the coming decades, a new round of scientific and technological revolution is expected in the world. A person will be surrounded by artificial intellectual systems based on knowledge — cognitive systems. The existing education system is focused on giving knowledge about previous generations of intelligent systems — IoT, CPS, and should be transformed. The required amount of knowledge can no longer be transferred to a trained specialist within the framework of existing teaching technologies. Therefore, skills of using, extracting and transforming knowledge become the basis of promising technologies of continuous self-education. To determine a direction of studying cognitive control systems, a model of a structure of such system is proposed, based on control levels. Each level of this model corresponds to procedures for transforming forms of knowledge that need to be studied by a future engineer. To favour the development of students’ self-education skills, it is suggested to sharply increase the amount of research assignments in the practice of teaching almost all technical curricula studied at universities. Examples of such tasks in physics, electrical engineering and other disciplines are given. Some of these examples are about “black box” objects; another need the application of a non-standard approach to ADC. Besides, a way of using ternary logic and logical inference to assess the quality of knowledge obtained by the cognitive control system is considered.
KeywordsCognitive control systems Models of cognitive control systems Research assignments Engineering education
This work was supported in part by the European Commission within the program “Tempus” “DesIRE — Development of Embedded System Courses with implementation of Innovative Virtual approaches for integration of Research, Education and Production in UA, GE, AM”, Grant No. 544091-TEMPUS-1-2013-1-BE-TEMPUS-JPCR as well as “Union Internet of Things: Emerging Curriculum for Industry and Human Application ALIOT”, Grand No. 573818-EPP-1-2016-1-UK-EPPKA2-CBHE-JP.
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