The Logic of AGM Learning from Partial Observations

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12005)


We present a dynamic logic for inductive learning from partial observations by a “rational” learner, that obeys AGM postulates for belief revision. We apply our logic to an example, showing how various concrete properties can be learnt with certainty or inductively by such an AGM learner. We present a sound and complete axiomatization, based on a combination of relational and neighbourhood version of the canonical model method.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.ILLCUniversity of AmsterdamAmsterdamThe Netherlands
  2. 2.ArchéUniversity of St. AndrewsSt AndrewsUK

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