Learning classifier systemLearning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy).
Learning theory (education)Learning theory describes how students receive, process, and retain knowledge during learning. Cognitive, emotional, and environmental influences, as well as prior experience, all play a part in how understanding, or a worldview, is acquired or changed and knowledge and skills retained. Behaviorists look at learning as an aspect of conditioning and advocate a system of rewards and targets in education.
Design-based learningDesign-based learning (DBL), also known as design-based instruction, is an inquiry-based form of learning, or pedagogy, that is based on integration of design thinking and the design process into the classroom at the K-12 and post-secondary levels. Design-based learning environments can be found across many disciplines, including those traditionally associated with design (e.g. art, architecture, engineering, interior design, graphic design), as well as others not normally considered to be design-related (science, technology, business, humanities).
