AICOJul 4, 2022

Refutation of Spectral Graph Theory Conjectures with Monte Carlo Search

arXiv:2207.03343v315 citationsh-index: 27
AI Analysis

This addresses a specific problem for researchers in graph theory by providing an efficient computational method, though it appears incremental as it applies existing algorithms to a new domain.

The paper tackled the problem of refuting spectral graph theory conjectures by using Monte Carlo Search algorithms to build graphs and find counter-examples quickly, achieving results in minutes.

We demonstrate how Monte Carlo Search (MCS) algorithms, namely Nested Monte Carlo Search (NMCS) and Nested Rollout Policy Adaptation (NRPA), can be used to build graphs and find counter-examples to spectral graph theory conjectures in minutes.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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