To delve deeper into the concepts explained in this chapter, you can refer to the following sources:
- Reinforcement Learning: An Introduction, Sutto R., Barto A. (2018), The MIT Press, licensed under the Creative Commons Attribution-NonCommercial-NoDeriv 2.0 Generic License (http://www.andrew.cmu.edu/course/10-703/textbook/BartoSutton.pdf)
- Machine Learning Projects, Chapter: Bias-Variance for Deep Reinforcement Learning: How To Build a Bot for Atari with OpenAI Gym (https://assets.digitalocean.com/books/python/machine-learning-projects-python.pdf)
- Reinforcement learning with ROS and Gazebo (https://ai-mrkogao.github.io/reinforcement%20learning/ROSRL)
- Testing different OpenAI RL algorithms with ROS And Gazebo (https://www.theconstructsim.com/testing-different-openai-rl-algorithms-with-ros-and-gazebo/)
- Extending the OpenAI Gym for robotics: a toolkit for reinforcement...
