A Modal Logic for Supervised Learning

Journal of Logic, Language and Information 31 (2):213-234 (2022)
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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. In this work, we develop a general framework—the supervised learning game—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 learning process, and she may also ignore the potential relation between different hypotheses; on the other hand, Teacher is able to correct Learner’s mistakes, eliminate potential mistakes and point out the facts ignored by Learner. To reason about strategies in this game, we develop a modal logic of supervised learning and study its properties. Broadly, this work takes a small step towards studying the interaction between graph games, logics and formal learning theory.

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Author Profiles

Alexandru Baltag
University of Amsterdam
Dazhu Li
Institute of Philosophy, Chinese Academy of Sciences

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References found in this work

Is Justified True Belief Knowledge?Edmund Gettier - 1963 - Analysis 23 (6):121-123.
Model Theory.Michael Makkai, C. C. Chang & H. J. Keisler - 1991 - Journal of Symbolic Logic 56 (3):1096.
Is Justified True Belief Knowledge?Edmund L. Gettier - 1963 - In Sven Bernecker & Fred I. Dretske (eds.), Knowledge: Readings in Contemporary Epistemology. Oxford University Press.

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