Indian Journal of Research and Development Systems in Technologization (IJRDST)

ISSN: 2584-2579 (Online)

APPLICATIONS OF REINFORCEMENT LEARNING IN DECISION MAKING

Author(s)

Sivakumar, R.D.

Assistant Professor, Department of Computer Science, Bell Institute, Sivakasi West.

Abstract

RL (Reinforcement learning) is a prevailing mechanism for training intelligent agents to handle choices in complex and chance environments. This article will give out a introduction of taking the advantage of reinforcement learning methods for variety application situations in the way of making decisions. In the first part, basic concepts of reinforcement learning (RL) will be introduced, and then the application of RL in sequential decision-making problems such as autonomous driving, robotics, finance, and gaming will be explored. This includes showing how RL algorithms let agents to learn the best policies through alongside the environment, whereas a rational agent balances exploration and exploitation activities to maximize the reward accumulation. Moreover it look at obstacles as well as future directions of reinforcement learning for decision making, such as scalability, sample efficiency and ethical concerns. This article focuses on stressing the multi-facet and future prospects of RL. The coverage of this article is with the hope that more work will be done on reinforcing learning for intelligent decision making in complicated real world cases.

Keywords : Reinforcement Learning, Decision Making, Sequential Decision Making, Autonomous Driving, Robotics, Ethical Considerations and Intelligent Agents.

Volume : 1

Issue : 1

Pages : 24-33

Date of Publication : March 2024

DOI

Published By

IJRDST

Published In

Indian Journal of Research and Development Systems in Technologization (IJRDST)