A parallelized RL search over graphs produces three new counterexamples to conjectured Laplacian spectral radius bounds, alongside a speedup claim that is only weakly supported.
Artificial intelligence and machine learning generated conjectures with TxGraffiti
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abstract
\emph{TxGraffiti} is a machine learning and heuristic based artificial intelligence designed to automate the task of conjecturing in mathematics. Since its inception, TxGraffiti has generated many surprising conjectures leading to publication in respectable mathematical journals. In this paper we outline the machine learning and heuristic techniques implemented by TxGraffiti. We also recall its contributions to the mathematical literature and announce a new online version of the program available for anyone curious to explore conjectures in graph theory.
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Reinforcement learning for graph theory, Parallelizing Wagner's approach
A parallelized RL search over graphs produces three new counterexamples to conjectured Laplacian spectral radius bounds, alongside a speedup claim that is only weakly supported.