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León Bohn

dblp:299/1407 · DBLP profile ↗
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3ranked-venue papers
3as first author
3since 2021 · last 2025
—ORCID · none

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

Theory of computation · 3 · 3 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Automata and formal languages · 56% Computational complexity · 24% Algorithms and data structures · 20%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures
learning algorithms
1.422025
Saturation Problems for Families of Automata · ICALP 2025
Passive Learning of Deterministic Büchi Automata by Combinations of DFAs · ICALP 2022
Computational complexity › decidability › decision problems for automata
decidability and complexity of automata problems
0.912025
Saturation Problems for Families of Automata · ICALP 2025
Automata and formal languages › finite automata
deterministic finite automata
0.912025
Saturation Problems for Families of Automata · ICALP 2025
Automata and formal languages › infinite words
omega-regular languages
0.912025
Saturation Problems for Families of Automata · ICALP 2025
Computational complexity › complexity classes › PSPACE
PSPACE-completeness
0.912025
Saturation Problems for Families of Automata · ICALP 2025
Automata and formal languages
saturation
0.912025
Saturation Problems for Families of Automata · ICALP 2025
Automata and formal languages › grammatical inference
automata learning
0.612022
Passive Learning of Deterministic Büchi Automata by Combinations of DFAs · ICALP 2022
Automata and formal languages › grammatical inference
passive learning
0.612022
Passive Learning of Deterministic Büchi Automata by Combinations of DFAs · ICALP 2022

Methods — techniques the papers use, named apart from their topics

polynomial-time algorithm · 0.9PSPACE upper bound · 0.9combination of DFAs · 0.6
YearPublicationVenuePosition
2025 Saturation Problems for Families of Automata
abstract
Families of deterministic finite automata (FDFA) represent regular ω-languages through their ultimately periodic words (UP-words). An FDFA accepts pairs of words, where the first component corresponds to a prefix of the UP-word, and the second component represents a period of that UP-word. An FDFA is termed saturated if, for each UP-word, either all or none of the pairs representing that UP-word are accepted. We demonstrate that determining whether a given FDFA is saturated can be accomplished in polynomial time, thus improving the known PSPACE upper bound by an exponential. We illustrate the application of this result by presenting the first polynomial learning algorithms for representations of the class of all regular ω-languages. Furthermore, we establish that deciding a weaker property, referred to as almost saturation, is PSPACE-complete. Since FDFAs do not necessarily define regular ω-languages when they are not saturated, we also address the regularity problem and show that it is PSPACE-complete. Finally, we explore a variant of FDFAs called families of deterministic weak automata (FDWA), where the semantics for the periodic part of the UP-word considers ω-words instead of finite words. We demonstrate that saturation for FDWAs is also decidable in polynomial time, that FDWAs always define regular ω-languages, and we compare the succinctness of these different models.
León Bohn, Yong Li 0031, Christof Löding, Sven Schewe
ICALP1
2022 Passive Learning of Deterministic Büchi Automata by Combinations of DFAs
abstract
International audience
León Bohn, Christof Löding
ICALP1
2021 Constructing Deterministic ω-Automata from Examples by an Extension of the RPNI Algorithm
León Bohn, Christof Löding
MFCS1