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 $[o]\phi$, as well as with a learning operator $L(\overrightarrow{o})$, which encodes the learner's conjecture after observing a finite sequence of data $\overrightarrow{o}$. We completely axiomatise DLLT, study its expressivity and use it to characterise various notions of knowledge, belief, and learning.

中文翻译：

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学习理论的动态逻辑

在将拓扑学习中的形式学习理论和动态认知逻辑联系起来的先前工作[4]，[5]的基础上，我们引入了动态学习逻辑理论（DLLT），以动态扩展了子集空间逻辑[18]，[10]观察方式 $[Ø]\phi$，以及学习运算符 $\mathrm{大号}（\overrightarrow{Ø}）$，它在观察有限的数据序列后对学习者的猜想进行编码$\overrightarrow{Ø}$。我们完全公信DLLT，研究其表现力并将其用于表征知识，信念和学习的各种概念。