Development of “embodied”
AI Robust against Real-World Unstructured Environments

Our goal is to develop artificial intelligence that is capable of learning from a small number of samples unevenly distributed in space and time and achieves intelligent processing of structured/unstructured and verbal/non-verbal data. We also will develop mathematical modeling and mathematical analysis methods that are able to work on real-world data robustly and extract invariant structures from them.