Automatic reasoning, decision-making, multi-agent systems, big data, and learning (automatic, human-assisted by computer, or preference-based) play a major role in the current challenges facing artificial intelligence and data science.

The Artificial Intelligence and Data Science Axe aims at structuring and coordinating research in these areas by promoting collaboration between the LIP6 teams. Its activities cover a broad spectrum of fundamental AI research and develop applications in various fields (health, education, simulation of real systems, transportation, etc.).

A first interdisciplinary research is related to data science and complex systems. It focuses on the design of models (mathematical and computational models of knowledge and reasoning or learning), approaches and tools capable of representing and analysing complex data, and scaling models up to promote their deployment in various scientific and application fields.

A second research focuses around explainable AI and human-centred AI systems. It aims at supporting the transition to an era where inferences, decisions and recommendations made by AI algorithms include Human users from the design to the use of the model for decision-making, promoting systems that are interpretable, justifiable, explainable, ethical and fair.

A third research area concerns the proposal of robust models and algorithms capable of handling inaccuracies, uncertainties and contextual changes over time.

A fourth research concerns AI@Edge. It focuses on techniques for embedding and computational optimisation of models, aiming at reducing energy consumption and increasing the autonomy of edge devices.