What are the applications of reinforcement learning?

The concept of reinforcement learning (RL) can be described as a type of machine learning where an agent is taught to make choices by interfacing with its environment, gaining feedback in the form of penalties or rewards and then improving its behavior in the course of time. Contrary to supervised learning where the model is taught by analyzing data that is labeled, RL focuses on learning by trial and trial and. This unique method has created RL useful in a broad array of real-world applications across different industries.

The most well-known uses of reinforcement learning are the field of robotics. Robots typically operate in a dynamic and unpredictable environment that do not have pre-programmed commands. RL allows robots to learn things like moving, grasping objects or maneuvering through spaces with no explicit programming. For example, robots powered by RL are able to learn how to select and put objects in warehouses, adjust for changes within their environment or even work alongside human workers in manufacturing environments.
https://www.sevenmentor.com/da....ta-science-course-in