SCOOL is a research group in machine learning.

SCOOL is dedicated to the study of the problem of sequential decision making in an uncertainty environment. We mostly focus on bandit and reinforcement learning problems. We aim at designing mathematically sound algorithms which performance enjoy formal properties, while taking into account the constraints due to realistic applications.

Regarding applications, we favor those related to health, sustainable development, in particular agriculture and agro-ecology. Our activities span the whole spectrum from fundamental research to transfer, through collaborations and contracts with private and academic partners.