Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Reinforcement Learning and Regret Bounds for Admission Control
Authors: Lucas Weber, Ana Busic, Jiamin Zhu
ICML 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental evaluations are conducted in section 7 |
| Researcher Affiliation | Collaboration | 1Inria and DI ENS, Ecole Normale Sup erieure, PSL University, Paris, France 2IFP Energies nouvelles, 1 et 4 avenue de Bois-Pr eau, 92852 Rueil-Malmaison, France. |
| Pseudocode | Yes | Algorithm 1 PI for Admission Control; Algorithm 2 VI for Admission Control; Algorithm 3 UCRL-AC |
| Open Source Code | Yes | Our code is available at: https://github.com/luweber21/ucrl-ac. |
| Open Datasets | No | The paper describes a simulated queuing system (M/M/c/S queue) and its parameters rather than using a conventional publicly available dataset. |
| Dataset Splits | No | The paper simulates a queuing system and does not specify train/validation/test splits as it does not rely on a conventional dataset. |
| Hardware Specification | Yes | The experiments were run on a Mac Book Pro 2021 equipped with an Apple M1 Pro processor and 16 GB RAM. |
| Software Dependencies | No | The paper does not specify version numbers for key software components or libraries used in the experiments. |
| Experiment Setup | Yes | We consider 5 servers, 2 job classes with immediate rewards R1 = 20 and R2 = 10 and arrival rates λ1 = 1 and λ2 = 1 respectively, and holding cost C(t) = 0.1t for both classes. For UCRL-AC, we used Λmin = 1 and Λmax = 4. |