SELF-LEARNING DECISIONAL INFORMATION SYSTEM FOR SECURITY (SL-D.I.S.S.) FOR HUMAN SPACE RXPLORATION MISSION

This paper presents a Self-Learning Decisional Information System for Security (SL-D.I.S.S.) dedicated to the Human Space Exploration Mission. The objective is to conceive a decisional information system for human long duration space flight (> 950 days) which will be realise in entire autonomy in the solar system. This article describes the importance of the ontological and epistemological context for designing an open multi-agent and reliable system able for self-adapt in dangerous and unforeseen situations. We present in link with our research, the limits of the empirical analytical paradigm and several paths of research lead by the nascent paradigm of enaction. The strong presumption is that classical ways of modelisation could not respond and challenge the security of a technical system which will support human exploration missions.