Introduction to a Learning General Theory

We explain the significance of a learning general theory. We work in a resolution informational level that is defined on a population. The populational magnitude changes through the creation or destruction of individual systems; we express this creation or destruction by means of the reproducibility, which produces a selective discrimination on the population. We define the reinforcement as far as a goal variable is concerned and separate the reinforcement by selective discrimination and the reinforcement by a change of the conditional probability. We also define memory accumulation and reinforcement on individual systems and study The effectiveness and the regularity of reinforcement in relation to the goal. We define the information on a variable and its learning; we study the relation between learning and reinforcement and the transference of learning. We define the controlled system and its information and study its learning. We define organized learning, with memory accumulation, and closed control. We introduce axiomatics and study their consequences, their testing through modeling, and the possible repercussions of the theory.