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Main Authors: Kortus, Tobias, Keidel, Ralf, Gauger, Nicolas R., Kieseler, Jan
Format: Recurso digital
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.18456346
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author Kortus, Tobias
Keidel, Ralf
Gauger, Nicolas R.
Kieseler, Jan
author_facet Kortus, Tobias
Keidel, Ralf
Gauger, Nicolas R.
Kieseler, Jan
contents <p>The artifacts included in this record complement the code repository available at <a href="https://github.com/SIVERT-pCT/marl-tracking" target="_new" rel="noopener">https://github.com/SIVERT-pCT/marl-tracking</a> and provide all necessary resources to reproduce the results and figures presented in [1]. These artifacts encompass trained models and supplementary files (e.g., loss landscape results) that support the execution of the experiments described in the repository. For comprehensive instructions on how to utilize this data, please consult the documentation provided at <a href="https://github.com/SIVERT-pCT/marl-tracking" target="_new" rel="noopener">https://github.com/SIVERT-pCT/marl-tracking</a>.</p> <p> </p> <p>[1] Kortus, T., Keidel, R., Gauger, N., Kieseler, J., on behalf of the Bergen pCT Collaboration (2026). Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning<em>. Machine Learning: Science and Technology, 7(1), 015021.<br></em></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18456346
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Supplementary Data for "Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning"
Kortus, Tobias
Keidel, Ralf
Gauger, Nicolas R.
Kieseler, Jan
<p>The artifacts included in this record complement the code repository available at <a href="https://github.com/SIVERT-pCT/marl-tracking" target="_new" rel="noopener">https://github.com/SIVERT-pCT/marl-tracking</a> and provide all necessary resources to reproduce the results and figures presented in [1]. These artifacts encompass trained models and supplementary files (e.g., loss landscape results) that support the execution of the experiments described in the repository. For comprehensive instructions on how to utilize this data, please consult the documentation provided at <a href="https://github.com/SIVERT-pCT/marl-tracking" target="_new" rel="noopener">https://github.com/SIVERT-pCT/marl-tracking</a>.</p> <p> </p> <p>[1] Kortus, T., Keidel, R., Gauger, N., Kieseler, J., on behalf of the Bergen pCT Collaboration (2026). Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning<em>. Machine Learning: Science and Technology, 7(1), 015021.<br></em></p>
title Supplementary Data for "Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning"
url https://doi.org/10.5281/zenodo.18456346