The theoretical framework and cognitive process of learning

Learning is a fundamental cognitive process of human intelligence. According to cognitive informatics, learning as a collective term can be classified into the categories of transitive, objective, and complex learning. This paper presents a theoretical framework of learning and explains its cognitive processes. The neural informatics foundations of learning, particularly the Hierarchical Neural Cluster (HNC) model and the Object-Attribute-Relation (OAR) model, are explored. The taxonomy and theory of learning are described based on Concept Algebra. The mathematical models of learning are systematically established for the categories of the transitive, objective, and complex learning. On the basis of the fundamental theories of learning, the cognitive processes of learning are formally described using Real-Time Process Algebra (RTPA). The theoretical framework established in this work can be applied to both human and machine learning systems.