About a framework for information and information processing of learning systems

The term `information', that is used in various contexts, might better be replaced with one that incorporates novelty, activity and learning. Many important communications of learning systems are non-ergodic. The ergodicity assumption in Shannon's communication theory restricts his and all related concepts to systems that can not learn. For learning systems that interact with their environments, the more primitive concept of `variety' needs to be used, instead of probability. Humans have a fundamental need for variety: they can't permanently perceive the same context, they can't always do the same things. The fundamental need for variety leads to a different interpretation of human behaviour that is often classified as "errors". Variety is the basis to measure complexity. Complexity in the relationship between a learning system and its context can be expressed as incongruity. Incongruity is the difference between internal complexity of a learning system and the complexity of the context. Traditional concepts of information processing are models of homeostasis on a basic level without learning. Activity and the irreversible learning process are driving forces that cause permanently in-homeostasis in the relationship between a learning system and its context. A suitable model for information processing of learning systems must be conceptualised on a higher level: a homeostatic model of `in-homeostasis'. A concept to information processing is presented that derives an inverted U-shaped function between incongruity and information. This concept leads to some design recommendations for man-machine systems