Matthias Lutter

dblp:195/8214 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2 · 1 since 2021Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
YearPublicationVenuePosition
2022 Learning residual alternating automata
Sebastian Berndt 0001, Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk
Inf. Comput.3
2019 Proper learning of k-term DNF formulas from satisfying assignments
Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk
J. Comput. Syst. Sci.2
2017 Learning Residual Alternating Automata
abstract
Residuality plays an essential role for learning finite automata. While residual deterministic and non-deterministic automata have been understood quite well, fundamental questions concerning alternating automata (AFA) remain open. Recently, Angluin, Eisenstat, and Fisman (2015) have initiated a systematic study of residual AFAs and proposed an algorithm called AL* – an extension of the popular L* algorithm – to learn AFAs. Based on computer experiments they have conjectured that AL* produces residual AFAs, but have not been able to give a proof. In this paper we disprove this conjecture by constructing a counterexample. As our main positive result we design an efficient learning algorithm, named AL** and give a proof that it outputs residual AFAs only. In addition, we investigate the succinctness of these different FA types in more detail.
Sebastian Berndt 0001, Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk
AAAI3