"Introduction" describes basic instructions as to what you need using Mind Render/AI Drill and how to set up the learning environment. Please read this part first.

[Table of Contents]
Chapter1 Preparation
　Install Unity Hub
　Install Unity
　Sign in to Unity
　Add a project
　Install Visual Studio Code
　Edit the program

Chapter2 Configure the learning environment
　Unity Screen Layout
　Configure the settings for self-driving cars
　　Open the scene from the Project
　　Set Agent in the Inspector
　　Set Sensor in the Inspector
　　Set QEnvironment in the Inspector (Q-learning)
　　Set NEEnvironment in the Inspector (Neuroevolution)
　Train the Agent (Q-learning, Neuroevolution)
　Display the learning status（Q-learning, Neuroevolution
　　Q-learning
　　Neuroevolution
　Save Learning Results
　Run Learning Results

"Python Cooperation" describes an example of writing the machine learning part for a self-driving program in Python. Chapter1 to 3 are the same as "Self Driving/Mind Render AI Drill".

[Table of Contents]
Chapter1 Self-Driving Car
　Overview of the Unity Scene
　　Car
　　Sensor
　　Checkpoints
　Overview of the Program
　Code of Self-Driving Cars
　　Action
　　Rewards
　　Observation of the Environment
　Optional Exercises

Chapter2 Reinforcement Learning
　Reinforcement Learning: A Definition
　Q-learning
　Code of Q-learning
　　Implementation of Q-learning
　Result
　Optional Exercises
　Function Approximation, Deep Reinforcement Learning

Chapter3 Neuroevolution
　Artificial Neural Networks
　　Sigmoid Neuron
　　Multilayer Perceptron
　　Code of the Neural Network
　Evolutionary Algorithms
　　Genetic Operators
　　Code of the Evolutionary Algorithm
　　Fitness
　　Mutation
　　Training Results
　Optional Exercises

Chapter4 Unity-Python Cooperation
How to use the Program
Program Files
Control Flow of Unity-Python Cooperation
Start-Up Part
Action Part
Learning Part
Communication Method between Unity and Python
Optional Exercises