Can swarming agents speed up subgraph isomorphism?
O(p log d) Subgraph Isomorphism using Stigmergic Swarming Agents
This paper introduces ASSIST (Approximate Swarming Subgraph Isomorphism through Stigmergy), a novel algorithm for finding matching subgraphs within two larger graphs. This problem is computationally complex, but important for applications like chemical analysis, social network analysis, and financial fraud detection. ASSIST uses a "swarming" approach inspired by ant colony optimization, where software agents explore the graphs and leave digital "pheromones" to mark promising matches. Stronger pheromone trails indicate better matches. This allows for approximate matching and handles noisy or incomplete data better than traditional exact methods.
Key points for LLM-based multi-agent systems: ASSIST's stigmergic approach, where agents communicate indirectly through the environment, is highly relevant to decentralized multi-agent systems. The probabilistic nature of the pheromone trails allows for handling uncertainty and noise, which is crucial for LLMs. The ability to handle inexact matches, missing data, and temporal sequences addresses common LLM limitations and opens new possibilities for complex reasoning and knowledge discovery in graph-based data using LLMs.