INTERLEAVE: A Faster Symbolic Algorithm for Maximal End Component Decomposition

Fuente: arXiv
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Main Authors: Bansal, Suguman, Singh, Ramneet
Format: Preprint
Published: 2025
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author Bansal, Suguman
Singh, Ramneet
author_facet Bansal, Suguman
Singh, Ramneet
contents This paper presents a novel symbolic algorithm for the Maximal End Component (MEC) decomposition of a Markov Decision Process (MDP). The key idea behind our algorithm INTERLEAVE is to interleave the computation of Strongly Connected Components (SCCs) with eager elimination of redundant state-action pairs, rather than performing these computations sequentially as done by existing state-of-the-art algorithms. Even though our approach has the same complexity as prior works, an empirical evaluation of INTERLEAVE on the standardized Quantitative Verification Benchmark Set demonstrates that it solves 19 more benchmarks (out of 379) than the closest previous algorithm. On the 149 benchmarks that prior approaches can solve, we demonstrate a 3.81x average speedup in runtime.
format Preprint
id arxiv_https___arxiv_org_abs_2505_20748
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle INTERLEAVE: A Faster Symbolic Algorithm for Maximal End Component Decomposition
Bansal, Suguman
Singh, Ramneet
Logic in Computer Science
Formal Languages and Automata Theory
Programming Languages
D.3.1; F.3.1; F.4.0
This paper presents a novel symbolic algorithm for the Maximal End Component (MEC) decomposition of a Markov Decision Process (MDP). The key idea behind our algorithm INTERLEAVE is to interleave the computation of Strongly Connected Components (SCCs) with eager elimination of redundant state-action pairs, rather than performing these computations sequentially as done by existing state-of-the-art algorithms. Even though our approach has the same complexity as prior works, an empirical evaluation of INTERLEAVE on the standardized Quantitative Verification Benchmark Set demonstrates that it solves 19 more benchmarks (out of 379) than the closest previous algorithm. On the 149 benchmarks that prior approaches can solve, we demonstrate a 3.81x average speedup in runtime.
title INTERLEAVE: A Faster Symbolic Algorithm for Maximal End Component Decomposition
topic Logic in Computer Science
Formal Languages and Automata Theory
Programming Languages
D.3.1; F.3.1; F.4.0
url https://arxiv.org/abs/2505.20748