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Authors: Maria Chernigovskaya ; Andrey Kharitonov and Klaus Turowski

Affiliation: Faculty of Computer Science, Otto von Guericke University, Magdeburg, Germany

Keyword(s): Reinforcement Learning, Deep Reinforcement Learning, Hyper-Parameter Optimization.

Abstract: Nowadays, meta-heuristic and machine learning algorithms are often used for a variety of tasks in cloud computing operations. The choice of hyper-parameter values has a direct impact on the performance of these algorithms, making Hyper-Parameter Optimization (HPO) an important research field for facilitating the widespread application of machine learning and meta-heuristics for problem-solving. Manual parameter- ization of these algorithms is an inefficient method, which motivates researchers to look for a new and more efficient approach to tackle this challenge. One such innovative approach is Deep Reinforcement Learning (DRL), which has recently demonstrated a lot of potential in solving complex problems. In this work, we aim to explore this topic more thoroughly and shed light on the application of DRL-based techniques in HPO, specifically for Machine Learning and Heuristics/Meta-heuristics-based algorithms. We approach the problem by conducting a systematic literature review of t he recently published literature and summarizing the results of the analysis. Based on the conducted literature review, within the selected sources, we identified 14 relevant publications and a clear research gap in the cloud-specific use case for HPO via DRL. (More)

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Paper citation in several formats:
Chernigovskaya, M., Kharitonov, A. and Turowski, K. (2023). A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms. In Proceedings of the 13th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-650-7; ISSN 2184-5042, SciTePress, pages 236-243. DOI: 10.5220/0011954300003488

@conference{closer23,
author={Maria Chernigovskaya and Andrey Kharitonov and Klaus Turowski},
title={A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms},
booktitle={Proceedings of the 13th International Conference on Cloud Computing and Services Science - CLOSER},
year={2023},
pages={236-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011954300003488},
isbn={978-989-758-650-7},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Cloud Computing and Services Science - CLOSER
TI - A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms
SN - 978-989-758-650-7
IS - 2184-5042
AU - Chernigovskaya, M.
AU - Kharitonov, A.
AU - Turowski, K.
PY - 2023
SP - 236
EP - 243
DO - 10.5220/0011954300003488
PB - SciTePress

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