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https://dx.doi.org/10.48550/ar...
Article . 2025
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How Concise are Chains of co-Büchi Automata?

Authors: Ehlers, Rüdiger;

How Concise are Chains of co-Büchi Automata?

Abstract

Chains of co-Büchi automata (COCOA) have recently been introduced as a new canonical model for representing arbitrary omega-regular languages. They can be minimized in polynomial time and are hence an attractive language representation for applications in which normally, deterministic omega-automata are used. While it is known how to build COCOA from deterministic parity automata, little is currently known about their relationship to automaton models introduced earlier than COCOA. In this paper, we analyze the conciseness of chains of co-Büchi automata. We show that even in the case that all automata in the chain are deterministic, chains of co-Büchi automata can be exponentially more concise than deterministic parity automata. We then answer the question if this conciseness is retained when performing Boolean operations (such as disjunction and conjunction) over COCOA by showing that there exist families of languages for which these operations lead to an exponential growth of the sizes of the automata. The families have the property that when representing them using deterministic parity automata, taking the disjunction or conjunction of them only requires a polynomial blow-up, which shows that Boolean operations over COCOA do not retain their conciseness in general.

In Proceedings GandALF 2025, arXiv:2509.13258

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Keywords

FOS: Computer and information sciences, Logic in Computer Science, Formal Languages and Automata Theory (cs.FL), F.1.1; F.4.3, Formal Languages and Automata Theory, Logic in Computer Science (cs.LO)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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