It aims to develop symbolic and numerical approaches, new strategies and models of control and decision support to apprehend the complexity of spatio-temporal systems that can be non-stationary, non-linear, multi-physical and multi-scale in nature offering a model approach (simulation, decision-making, analytical) to address the thematic issues of the research unit.
These thematic issues raise disciplinary issues in computer science and mathematics, thus shifting the boundaries of these disciplines by extending modeling to other disciplines in the Humanities and Social Sciences, Earth and Life Sciences, allowing continuity in the chains of reasoning and construction from the most symbolic/abstract to the most numerical/concrete and reciprocally.
The choice of dimensions, spatialization and temporality of the data as well as the processes of interaction Society-Environment considered remain a challenge in modeling towards a decision aid. This group integrates the specification, modeling and analysis of spatio-temporal, multi-scale, multi-physical models based on observations and experiments on real complex systems. It implements several approaches bringing together the research lab’s expertise:
1) Methods for clarifying knowledge that can use existing ontologies or generate new ones,
2) Decision support methods that can be based on artificial intelligence concepts: intelligent control, learning, constrained optimization, etc.,