How to model consciousness in Memory Evolutive Systems?

Memory Evolutive Systems (MES) represent a mathematical model, based on Category Theory, to study natural open autonomous systems such as biological, neural or social systems. It has been progressively developed by the authors in a series of papers since 1986. In this model the dynamics is modulated by the competitive interactions between a net of internal more or less complex organs of regulation, called CoRegulators (CR), with a differential access to a central hierarchical Memory. This article attempts to model the notions of Semantics and Consciousness in such a MES A Semantics will emerge through the detection of specific invariances by the CRs that leads to classify objects according to their main attributes, and record the invariance classes. The model explains how it relies on a hierarchical 2 steps process: first a pragmatically 'acted' classification at the level of specific attributes (such as colors), then this classification is 'reflected' and analyzed at a higher level, and a new formal unit, called a 'concept', is formed to represent the invariance class (e.g., the color 'blue'). The introduction of more and more abstract concepts gives more flexibility to the comportment. It is essential for the development of some kind of 'consciousness'. A 'conscious' CR is characterized by the capacity to respond to a new event or to a fracture by an increase in awareness, which permits: (i) to extend its actual 'landscape' (formed by the information it can gather) retrospectively to past lower levels; (ii) to operate an abduction process in this extended landscape to find possible causes of the fracture; (iii) and finally to planify a strategy for several steps ahead, through the formation of internal 'virtual' landscapes in which strategies can be tried without energy costs. Thus consciousness would amount to an internalization of Semantics and Time, giving a selective advantage. In the second Part of the paper, a MES modeling a neural system is explicitly described and it is shown how the various processes described above are in agreement with present neurophysiological knowledge. Finally the general ideas are illustrated on a concrete example