References & Citations
Mathematics > Combinatorics
Title: Reinforcement learning for graph theory, I. Reimplementation of Wagner's approach
(Submitted on 27 Mar 2024 (v1), last revised 30 Mar 2024 (this version, v2))
Abstract: We reimplement here the recent approach of Adam Zsolt Wagner [arXiv:2104.14516], which applies reinforcement learning to construct (counter)examples in graph theory, in order to make it more readable, more stable and much faster. The presented concepts are illustrated by constructing counterexamples for a number of published conjectured bounds for the Laplacian spectral radius of graphs.
Submission history
From: Dragan Stevanovic [view email][v1] Wed, 27 Mar 2024 10:35:41 GMT (4593kb,D)
[v2] Sat, 30 Mar 2024 10:47:13 GMT (4593kb,D)
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