Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and 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 78 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 24 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 120 tok/s Pro
Kimi K2 193 tok/s Pro
GPT OSS 120B 459 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Propositional Encodings of Acyclicity and Reachability by using Vertex Elimination (2105.12908v1)

Published 27 May 2021 in cs.AI

Abstract: We introduce novel methods for encoding acyclicity and s-t-reachability constraints for propositional formulas with underlying directed graphs. They are based on vertex elimination graphs, which makes them suitable for cases where the underlying graph is sparse. In contrast to solvers with ad hoc constraint propagators for acyclicity and reachability constraints such as GraphSAT, our methods encode these constraints as standard propositional clauses, making them directly applicable with any SAT solver. An empirical study demonstrates that our methods together with an efficient SAT solver can outperform both earlier encodings of these constraints as well as GraphSAT, particularly when underlying graphs are sparse.

Citations (9)

Summary

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

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions 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.