Reinforcement Learning in Real Life Applications

 Reinforcement Learning in Real Life Applications

Pratham Shimpi

SY MCA

PES Modern College of Engineering,

Pune – 411005 Maharashtra, India

Prof. Mugdha Dharmadhikari

 PES Modern College of Engineering,

Pune – 411005 Maharashtra, India

Abstract— Reinforcement Learning is a crucial subset of machine learning that enables agents to learn decision-making through interaction with their environments, guided by feedback like rewards or penalties. This paper delves into Reinforcement Learning's applications across diverse sectors such as robotics, finance, healthcare, and gaming. In robotics, Reinforcement Learning facilitates tasks like object manipulation and environmental adaptation. In finance, it aids in portfolio management and trading strategy development, adapting to market dynamics. In healthcare, Reinforcement Learning assists in generating personalized treatment plans and analyzing medical images. Meanwhile, the gaming industry benefits from Reinforcement Learning -driven intelligent agents capable of challenging human players. Throughout, we explore Reinforcement Learning's fundamental principles, core components, and its transformative potential across these real-world applications.

Keywords—Reinforcement Learning, Decision-Making, Adaptive Agents.