Information and meaning are present everywhere around us and within ourselves. Specific studies have been implemented to link information and meaning (Linguistic, Biosemiotic, Psychology, Psychiatry, Cognition, Artificial Intelligence... ). No general coverage is available for the notion of meaning. We propose to complement this lack by a system approach to meaning generation in an evolutionary background. That short paper is a summary of the system approach where a Meaning Generator System (MGS) based on internal constraint satisfaction has been introduced. The MGS can be used for animals (with “stay alive” related constraints), for humans (with “look for happiness” type constraints) and for artificial agents with programmed constraints. Definitions for agency and autonomy are made available based on internal constraint satisfaction. Usage of the MGS with the Turing Test shows why today computers cannot think like humans do. The MGS also allows to introduces evolutionary scenarios for cognition, intentionality and self-consciousness, with an entry point to a human specific anxiety.
Continuations are proposed.