In this chapter, we will explore the world of machine learning through the following topics:
- Predicting actions with an N-Gram predictor
- Improving the predictor: Hierarchical N-Gram
- Learning to use a Naïve Bayes classifier
- Learning to use decision trees
- Learning to use reinforcement
- Learning to use artificial neural networks
In this chapter, we will explore the field of machine learning. This is a very extensive and intrinsic field in which even AAA titles have a hard time due to the amount of time that the techniques require for fine-tuning and experimentation.
However, the recipes that are contained in this chapter will give us a great head start in our endeavor to learn and apply machine-learning techniques to our games. They are used in several different ways, but the one we usually appreciate the most is difficulty adjustment.
Finally, you are advised to complement the recipes with the reading of more formal books on the subject, in order to gain theoretical insights that lie beyond the scope of this chapter.