A Second-Order Adaptive Network Model for Learner-Controlled Mental Model Learning Processes

Rajesh Bhalwankar, Jan Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Learning new knowledge or a new skill usually requires the development of an ade-quate internal mental model in the form of a mental network. The learning process for such an internal model involves (first-order) mental network adaptation. Such a learning process often integrates different elements, such as learning by observation and learning by instruction. For an effective learning process, a main issue is to get an appropriate timing of the different elements. To control the timing of these elements of a learning process, the mental network adaptation process has to be adaptive itself: second-order mental network adaptation. The second-order adaptive mental network model proposed here addresses this, where the first-order adaptation process models the learning pro-cess of mental network models and the second-order adaptation process controls the timing of the elements of the learning process. It is illustrated for learner-controlled mental model learning in the context of driving a car where the learner is in control of the integration of learning by observation and learning by instruction.
Original languageEnglish
Title of host publication Proc. of the 9th International Conference on Complex Networks and their Applications
PublisherSpringer Nature Switzerland AG
Publication statusAccepted/In press - 30 Sep 2020

Publication series

NameStudies in Computational Intelligence
PublisherSpringer Nature

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