Normal Forms for (Semantically) Witness-Based Learners in Inductive Inference
Vanja Dosko\v{c}, Timo K\"otzing

TL;DR
This paper investigates witness-based learners in inductive inference, establishing normal forms and equivalences among different paradigms, thereby deepening understanding of their computational power and relationships.
Contribution
It provides the first comprehensive normal forms for witness-based learners under syntactic and semantic convergence, and shows equivalences among various learning paradigms.
Findings
Witness-based learners are as powerful as non-witness-based in certain settings.
Normal forms for syntactic and semantic convergence are established.
Set-driven and Gold-style learners are equally powerful in semantic learning.
Abstract
We study learners (computable devices) inferring formal languages, a setting referred to as language learning in the limit or inductive inference. In particular, we require the learners we investigate to be witness-based, that is, to justify each of their mind changes. Besides being a natural requirement for a learning task, this restriction deserves special attention as it is a specialization of various important learning paradigms. In particular, with the help of witness-based learning, explanatory learners are shown to be equally powerful under these seemingly incomparable paradigms. Nonetheless, until now, witness-based learners have only been studied sparsely. In this work, we conduct a thorough study of these learners both when requiring syntactic and semantic convergence and obtain normal forms thereof. In the former setting, we extend known results such that they include…
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