This chapter presents a set of algorithms that underlie the various AI innovations and applications that are discussed in the rest of the book. This includes methods for tree search, evolutionary computation, unsupervised learning, supervised learning, deep learning, and reinforcement learning. It also gives a brief overview of behavior authoring methods, such as behavior trees, that are common for controlling agents in games. The algorithms are described with a focus on getting the key ideas across, and many of them include pseudocode, but no actual program code. However, the chapter includes ample pointers to other sources for those who wish to read more about specific algorithms. While this chapter is intended as a refresher for readers who already have a working knowledge of AI, it could be used as a mini-textbook in its own right.