Reinforcement learning, along with supervised and unsupervised learning, is one of three fundamental machine learning paradigms.

Reinforcement Learning is the most popular and emerging type of Machine Learning Algorithm. It is used in a variety of autonomous systems, including automobiles and industrial robotics. This algorithm's goal is to achieve a goal in a dynamic environment. It can achieve this goal thanks to several rewards provided by the system.

It is most commonly employed in the programming of robots to perform autonomous actions. It is also used in the development of intelligent self-driving cars.

Consider the example of robotic navigation.

Furthermore, further experimentation with the agent in its environment can improve its efficiency. This is the fundamental principle underlying reinforcement learning.

There are similar sequences of action in a reinforcement learning model.