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Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. [1]
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Template learning: Once a resonance occurs, for each channel ck, the weight vector is modified according to a learning rule which moves it towards the input pattern. When an uncommitted node is selected for learning, it becomes committed and a new uncommitted node is added to the field. Fusion ART thus expands its network architecture ...
ACT-R (pronounced /ˌækt ˈɑr/; short for "Adaptive Control of Thought—Rational") is a cognitive architecture mainly developed by John Robert Anderson and Christian Lebiere at Carnegie Mellon University. Like any cognitive architecture, ACT-R aims to define the basic and irreducible cognitive and perceptual operations that enable the human ...
Among the most used adaptive algorithms is the Widrow-Hoff’s least mean squares (LMS), which represents a class of stochastic gradient-descent algorithms used in adaptive filtering and machine learning. In adaptive filtering the LMS is used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean ...
Adaptive skills allow for safer exploration because they provide the learner with an increased awareness of their surroundings and of changes in context, that require new adaptive responses to meet the demands and dangers of that new context. Adaptive skills may generate more opportunities to engage in meaningful social interactions and acceptance.