Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python

Learn how to build a custom reinforcement learning environment using OpenAI Gym and Python in this 25-minute tutorial. Discover the process of creating a basic custom environment class, including setting up the __init__, step, and reset methods. Train a simple RL model using Keras-RL to interact with your custom environment. Follow along as the instructor demonstrates cloning baseline code, designing a custom environment blueprint, installing dependencies, and implementing key methods. Test your custom environment, train a DQN agent, and run it on your newly created setup. Gain practical skills for developing specific Python RL environments tailored to your projects in the field.