Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 75 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 20 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 193 tok/s Pro
GPT OSS 120B 467 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

On the Power of Finite Ambiguity in Büchi Complementation (2109.12828v2)

Published 27 Sep 2021 in cs.FL

Abstract: In this work, we exploit the power of \emph{finite ambiguity} for the complementation problem of B\"uchi automata by using reduced run directed acyclic graphs (DAGs) over infinite words, in which each vertex has at most one predecessor; these reduced run DAGs have only a finite number of infinite runs, thus obtaining the finite ambiguity in B\"uchi complementation. We show how to use this type of reduced run DAGs as a unified tool to optimize both rank-based and slice-based complementation constructions for B\"uchi automata with a finite degree of ambiguity. As a result, given a B\"uchi automaton with $n$ states and a finite degree of ambiguity, the number of states in the complementary B\"uchi automaton constructed by the classical rank-based and slice-based complementation constructions can be improved from $2{\mathsf{O}(n \log n)}$ and $\mathsf{O}((3n){n})$ to $\mathsf{O}(6{n}) \subseteq 2{\mathsf{O}(n)}$ and $\mathsf{O}(4{n})$, respectively. We further show how to construct such reduced run DAGs for limit deterministic B\"uchi automata and obtain a specialized complementation algorithm, thus demonstrating the generality of the power of finite ambiguity.

Citations (1)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube