Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence

Year : 2024 | Volume :11 | Issue : 01 | Page : 17-22
By

Prashant J. Viradiya

Amit M. Goswami

Hirenkumar K. Mistry

  1. Assistant Professor Department of Computer Engineering, Research Scholar, Gyanmanjari Innovative University (GMIU), Bhavnagar Gujarat India
  2. Software Engineer IT Department, Source Infotech Inc.,Edison NJ 08820 United States
  3. Software Engineer IT Department, PayPal, Saint Louis MO United States

Abstract

This work provides an overview of Reinforcement Learning (RL), an important field of artificial intelligence (AI) aims to provide the long-term benefits by learning a relating with a given environment. It spells out everything, what agents and environments do, to how rewards, states, and behaviours. It spent lot of time on looking the most usable RL algorithms, like DQN, SARSA, and Q-Learning. These studies provide a clear view of RL. It can be used in real life in many areas, like healthcare, robots, games, and self-driving cars. It provides a new idea for AlphaGo and self-driving warehouse robots to do this. Along with this probable future uses and study gaps, new developments in RL are also shown. The last part on talks about the effects of RL and how it might be used in the future. The study’s main objective is to give a short summary of RL, by including its current state, problems, and possible future directions, with a focus on how it changed over time help to make a technology better.

Keywords: Reinforcement Learning, Q-Learning, Robotics, Artificial Intelligence, SARSA, Deep Q-Networks.

[This article belongs to E-Commerce for Future & Trends(ecft)]

How to cite this article: Prashant J. Viradiya, Amit M. Goswami, Hirenkumar K. Mistry. Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence. E-Commerce for Future & Trends. 2024; 11(01):17-22.
How to cite this URL: Prashant J. Viradiya, Amit M. Goswami, Hirenkumar K. Mistry. Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence. E-Commerce for Future & Trends. 2024; 11(01):17-22. Available from: https://journals.stmjournals.com/ecft/article=2024/view=135718





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Regular Issue Subscription Review Article
Volume 11
Issue 01
Received January 17, 2024
Accepted February 13, 2024
Published March 28, 2024