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Why reinforcement learning?

Aydin, Mehmet Emin; Durgut, Rafet; Rakib, Abdur

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Authors

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Dr Mehmet Aydin Mehmet.Aydin@uwe.ac.uk
Senior Lecturer in Networks and Mobile Computing

Rafet Durgut

Abdur Rakib



Abstract

The term Artificial Intelligence (AI) has come to be one of the most frequently expressed keywords around the globe. Machine learning (ML) continues to gain popularity in the provision of solutions to both industrial and everyday problems, and advancements in infrastructure computing technologies have driven a surge of interest in AI, ML, and particularly large language models (LLMs). This involves huge data stocks and bulky data processing. However, many real-world problems lack the necessary existing data for modelling and model training. Furthermore, numerous dynamic problems do not retain data for later use due to constantly evolving circumstances, resulting in significant challenges in identifying or uncovering patterns (domain knowledge) within such dynamic structures and situations. These problems remain as significant and outstanding challenges.

Citation

Aydin, M. E., Durgut, R., & Rakib, A. (2024). Why reinforcement learning?. Algorithms, 17(6), Article 269. https://doi.org/10.3390/a17060269

Journal Article Type Editorial
Acceptance Date Jun 17, 2024
Online Publication Date Jun 20, 2024
Publication Date Jun 20, 2024
Deposit Date Jul 5, 2024
Publicly Available Date Jul 8, 2024
Journal Algorithms
Electronic ISSN 1999-4893
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 17
Issue 6
Article Number 269
DOI https://doi.org/10.3390/a17060269
Public URL https://uwe-repository.worktribe.com/output/12113661

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