In this chapter, we learned about the basic concepts of reinforcement learning and how to use these techniques to control a mechanical system. To start with, an overview of robot control was addressed.
Then, the OpenAI Gym library was introduced, which helps us to implement algorithms based on reinforcement learning. It includes a growing collection of benchmark issues that expose a common interface, and a website where people can share their results and compare algorithm performance. We explored the different environments that are available and how to install the library.
Finally, the CartPole system was used to implement Q-learning and Deep Q-learning algorithms. The CartPole system is a classic problem of reinforced learning. The system consists of a pole (which acts like an inverted pendulum) that's attached to a cart via a joint. The system is controlled by applying...
