5 citations · 9 across the 12 of their papers we have counts for
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cs.FL2020
Learning Languages in the Limit from Positive Information with Finitely Many Memory Changes
Timo Kötzing, Karen Seidel
We investigate learning collections of languages from texts by an inductive inference machine with access to the current datum and a bounded memory in form of states. Such a bounde…
cs.FL2018★ 2 cited
Learning from Informants: Relations between Learning Success Criteria
Martin Aschenbach, Timo Kötzing, Karen Seidel
Learning from positive and negative information, so-called \emph{informants}, being one of the models for human and machine learning introduced by E.~M.~Gold, is investigated. Part…