Abstract
Building on previous work [4,5] 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 [18,10] with dynamic observation modalities[o]φ, as well as with a learning operatorL(o→), which encodes the learner's conjecture after observing a finite sequence of data o→. We completely axiomatise DLLT, study its expressivity and use it to characterise various notions of knowledge, belief, and learning.
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