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 175 tok/s
Gemini 2.5 Pro 54 tok/s Pro
GPT-5 Medium 27 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 96 tok/s Pro
Kimi K2 196 tok/s Pro
GPT OSS 120B 464 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Place Bisimilarity is Decidable, Indeed! (2104.01392v5)

Published 3 Apr 2021 in cs.LO

Abstract: Place bisimilarity $\sim_p$ is a behavioral equivalence for finite Petri nets, originally proposed in \cite{ABS91}, that, differently from all the other behavioral relations proposed so far, is not defined over the markings of a finite net, rather over its places, which are finitely many. Place bisimilarity $\sim_p$ was claimed decidable in \cite{ABS91}, but its decidability was not really proved. We show that it is possible to decide $\sim_p$ with a simple algorithm, which essentially scans all the place relations (which are finitely many) to check whether they are place bisimulations. We also show that $\sim_p$ does respect the intended causal semantics of Petri nets, as it is finer than causal-net bisimilarity \cite{Gor22}. Moreover, we propose a slightly coarser variant, we call d-place bisimilarity $\sim_d$, that we conjecture to be the coarsest equivalence, fully respecting causality and branching time (as it is finer than fully-concurrent bisimilarity \cite{BDKP91}), to be decidable on finite Petri nets. Finally, two even coarser variants are discussed, namely i-place and i-d-place bisimilarities, which are still decidable, do preserve the concurrent behavior of Petri nets, but do not respect causality. These results open the way towards formal verification (by equivalence checking) of distributed systems modeled by finite Petri nets.

Citations (6)

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.

Authors (1)

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

Collections

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

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