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Main Author: Parunak, H. Van Dyke
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2601.02449
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author Parunak, H. Van Dyke
author_facet Parunak, H. Van Dyke
contents Maximum partial subgraph isomorphism compares two graphs (nodes joined by edges) to find a largest common subgraph. A common use case, for graphs with labeled nodes, seeks to find instances of a \textit{query} graph with $q$ nodes in a (typically larger) \textit{data} graph with $d$ nodes. The problem is NP-complete, and naïve solutions are exponential in $q + d$. The fastest current heuristic has complexity $O(d^2)$. This paper outlines ASSIST (Approximate Swarming Subgraph Isomorphism through Stigmergy), inspired by the ant colony optimization approach to the traveling salesperson. After peering (identifying matching individual nodes in query and data) in time $O(q\cdot log(d))$, the time required for ASSIST's iterative subgraph search, the combinatorially complex part of the problem, is linear in query size and constant in data size. ASSIST can be extended to support matching problems (such as temporally ordered edges, inexact matches, and missing nodes or edges in the data graph) that frustrate other heuristics.
format Preprint
id arxiv_https___arxiv_org_abs_2601_02449
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Stigmergic Swarming Agents for Fast Subgraph Isomorphism
Parunak, H. Van Dyke
Multiagent Systems
Discrete Mathematics
G.2.2; I.2.11
Maximum partial subgraph isomorphism compares two graphs (nodes joined by edges) to find a largest common subgraph. A common use case, for graphs with labeled nodes, seeks to find instances of a \textit{query} graph with $q$ nodes in a (typically larger) \textit{data} graph with $d$ nodes. The problem is NP-complete, and naïve solutions are exponential in $q + d$. The fastest current heuristic has complexity $O(d^2)$. This paper outlines ASSIST (Approximate Swarming Subgraph Isomorphism through Stigmergy), inspired by the ant colony optimization approach to the traveling salesperson. After peering (identifying matching individual nodes in query and data) in time $O(q\cdot log(d))$, the time required for ASSIST's iterative subgraph search, the combinatorially complex part of the problem, is linear in query size and constant in data size. ASSIST can be extended to support matching problems (such as temporally ordered edges, inexact matches, and missing nodes or edges in the data graph) that frustrate other heuristics.
title Stigmergic Swarming Agents for Fast Subgraph Isomorphism
topic Multiagent Systems
Discrete Mathematics
G.2.2; I.2.11
url https://arxiv.org/abs/2601.02449