Reinforcement Learning: A Comprehensive Overview

Authors

  • Priyanka Makkar Assistant Professor, Department of Computer Science & Engineering, Amity University, Gurugram, Haryana, India

Keywords:

Artificial Intelligence, Machine Learning, Reinforcement Learning, Algorithms, Applications

Abstract

Machine Learning is one of the most essential parts of Artificial Intelligence. Machine learning now exists as an important innovation and has a sufficient number of uses. Reinforcement Learning is one of the largest Machine Learning applications that enable machines and software agents to work more precisely and resolve behaviors within a specific context in order to maximize their performance. The self-improvement feature, web-based learning, and minimal effort of Strengthening Learning helped the machines become smart agents in basic technology. With the development of robust and effective algorithms, there is still a lot of work to be done. Therefore, the main purpose of this study is to provide Confirmation Learning reviews and applications using various algorithms from a machine learning perspective.

References

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Published

2024-03-30

How to Cite

[1]
P. Makkar, “Reinforcement Learning: A Comprehensive Overview”, IJIRCST, vol. 12, no. 2, pp. 119–125, Mar. 2024.

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