Learning and Dynamic Logic

In recent years, modern machine learning systems have shown unprecedented success at learning from data with little human guidance. In parallel to the advancements in AI, Cognitive Science has been very successful at applying a variety of computational models to human learning. Still, computational and cognitive learners are often ‘black-boxes’ lacking interpretation and explanation. How can we reason about, understand, and guide computational learning processes? This course focuses on a particular approach to this problem of describing and reasoning about learning which takes inspiration from Dynamic Epistemic Logic. the lectures will concern both classical problems in learning and recent results about dynamic logics of learning. The course will be interdisciplinary,  touching on themes from mathematical logic, theoretical computer science, and formal philosophy, but also cognitive and social science.