A Recent Publications Survey on Reinforcement Learning for Selecting Parameters of Meta-Heuristic and Machine Learning Algorithms

Maria Chernigovskaya, Andrey Kharitonov, Klaus Turowski

2023

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 the 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.

Paper Citation

in Harvard Style

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 - Volume 1: CLOSER, ISBN 978-989-758-650-7, SciTePress, pages 236-243. DOI: 10.5220/0011954300003488

in Bibtex Style

@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 - Volume 1: CLOSER,},
year={2023},
pages={236-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011954300003488},
isbn={978-989-758-650-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Cloud Computing and Services Science - Volume 1: 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
AU - Chernigovskaya M.
AU - Kharitonov A.
AU - Turowski K.
PY - 2023
SP - 236
EP - 243
DO - 10.5220/0011954300003488
PB - SciTePress