TensorBoard runs for reinforcement learning on automated conjectured bounds on Laplacian spectral radius of graphs
<p>The zip archive contains separate folders with TensorBoard event files for the runs of our reinforcement learning implementation on the conjectured upper bounds for the Laplacian spectral radius, which are listed in Appendix B of the forthcoming paper: S. Al-Yakoob, M. Ghebleh, A. Kanso, D. Stevanović, Reinforcement learning for graph theory, I. Reimplementation of Wagner’s approach, Art Discrete Appl. Math. (2024).</p> <p>To view the contained graphs and the evolution of rewards, unzip the archive in a folder of your choice, and run in the terminal the command "tensorboard --logdir runs" from the parent folder of the unzipped "runs" folder.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4