FoLiReL

Foundations of Lifelong Reinforcement Learning

01/01/2023 to 31/12/2028

A major, challenging problem that arises in Artificial Intelligence (AI) is that of allowing machines to automatically and efficiently reuse past experience. In the Machine Learning parlance, Meta-Learning, is the ability of an agent to acquire skills across tasks, and relies on a long-term definition of the loss function which averages the learner’s risk over tasks and entice them to learn high-level, generalizable concepts. This goal is multifaceted, especially in an online and interactive learning setting such as Reinforcement Learning.