Speaker: Dazhu Li
Date and Time: Thursday, January 23rd 2020, 17:00-18:30
(Note the unusual starting time)
Venue: ILLC Seminar Room F1.15, Science Park 107.
Title: On the Right Path: A Modal Logic for Supervised Learning.
Abstract. Formal learning theory formalizes the process of inferring a general result from examples, as in the case of inferring grammars from sentences when learning a language. Although empirical evidence suggests that children can learn a language without responding to the correction of linguistic mistakes, the importance of Teacher in many other paradigms is significant. Instead of focusing only on learner(s), this work develops a general framework — supervised learning game (SLG) — to investigate the interaction between Teacher and Learner. In particular, our proposal highlights several interesting features of the agents: on the one hand, Learner may make mistakes in the process of learning, and she may also ignore the potential relation between different hypotheses; on the other hand, Teacher is able to correct Learner’s mistakes, eliminate Learner’s mistakes and point out the facts ignored by Learner. To reason about strategies in this game, we develop a modal logic of supervised learning (SLL), and study its properties. Broadly, this work takes a small step toward studying the interaction between graph games, logics and formal learning theory.