Rate the Article: Unravelling the Complexity: Understanding the Challenges of Reinforcement Learning, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

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Research Paper | Computer Science & Engineering | India | Volume 13 Issue 3, March 2024 | Rating: 4.8 / 10


Unravelling the Complexity: Understanding the Challenges of Reinforcement Learning

Brahmaleen Kaur Sidhu


Abstract: After an extensive research and exploration of supervised, unsupervised and semi-supervised machine learning algorithms, researchers across the numerous application domains of machine learning are now looking to implement reinforcement learning techniques as they promise a realization of more human-like intelligence in machines. This paper presents a comprehensive body of knowledge about the complexities and challenges that researchers might face while developing reinforcement learning models as solutions for real-life problems. Also, some recommendations have been made in order to assist effective implementation of reinforcement learning algorithms.


Keywords: computational complexity, environment specification, exploration-exploitation, reinforcement learning, safeRL, sample efficiency


Edition: Volume 13 Issue 3, March 2024,


Pages: 233 - 239



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