A Dynamic Logic for Learning Theory

Alexandru Baltag, Nina Gierasimczuk, Aybüke Özgün, Ana Lucia Vargas Sandoval, Sonja Smets

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Abstract

Building on previous work that bridged Formal Learning Theory and Dynamic Epistemic Logic in a topological setting, we introduce a Dynamic Logic for Learning Theory (DLLT), extending Subset Space Logics with dynamic observation modalities, as well as with a learning operator, which encodes the learner’s conjecture after observing a finite sequence of data. We completely axiomatise DLLT, study its expressivity and use it to characterise various notions of knowledge, belief, and learning. 
Original languageEnglish
Title of host publication Dynamic Logic. New Trends and Applications. : First International Workshop, DALI 2017, Brasilia, Brazil, September 23-24, 2017, Proceedings
EditorsAlexandre Madeira, Mario Benevides
Volume10669
PublisherSpringer
Publication date2018
Pages35-54
ISBN (Electronic)978-3-319-73579-5
DOIs
Publication statusPublished - 2018
EventDaLi - Dynamic Logic: new trends and applications 2017 - Brasilia, Brazil
Duration: 23 Sep 201724 Sep 2017
Conference number: 1st

Workshop

WorkshopDaLi - Dynamic Logic: new trends and applications 2017
Number1st
CountryBrazil
CityBrasilia
Period23/09/201724/09/2017
SeriesLecture Notes in Computer Science
ISSN0302-9743

Keywords

  • Learning theory
  • Dynamic epistemic logic
  • Modal Logic
  • Subset Space Semantics
  • Inductive knowledge
  • Epistemology

Cite this

Baltag, A., Gierasimczuk, N., Özgün, A., Vargas Sandoval, A. L., & Smets, S. (2018). A Dynamic Logic for Learning Theory. In A. Madeira, & M. Benevides (Eds.), Dynamic Logic. New Trends and Applications. : First International Workshop, DALI 2017, Brasilia, Brazil, September 23-24, 2017, Proceedings (Vol. 10669, pp. 35-54). Springer. Lecture Notes in Computer Science https://doi.org/10.1007/978-3-319-73579-5_3