What this book covers
Chapter 1, Behaviors – Intelligent Movement, explores some of the most interesting movement algorithms based on the steering behavior principles developed by Craig Reynolds along with work from Ian Millington. They act as a foundation for most of the AI used in advanced games and other algorithms that rely on movement, such as the family of path-finding algorithms.
Chapter 2, Navigation, explores path-finding algorithms for navigating complex scenarios. It will include some ways to represent the world using different kinds of graph structures, and several algorithms for finding a path, each aimed at different situations.
Chapter 3, Decision Making, shows the different decision-making techniques that are flexible enough to adapt to different types of games, and robust enough to let us build modular decision-making systems.
Chapter 4, Coordination and Tactics, deals with a number of different recipes for coordinating different agents as a whole organism, such as formations and techniques that allow us make tactical decisions based on graphs, such as waypoints and influence maps.
Chapter 5, Agent Awareness, deals with different approaches of simulating sense stimuli on an agent. We will learn how to use tools that we already know to create these simulations, colliders, and graphs.
Chapter 6, Board Games AI, explains a family of algorithms for developing board-game techniques to create artificial intelligence.
Chapter 7, Learning Techniques, explores the field of machine learning. It will give us a great head start in our endeavor to learn and apply machine-learning techniques to our games.
Chapter 8, Miscellaneous, introduces new techniques and uses algorithms that we have learned about in previous chapters in order to create new behaviors that don't quite fit in a definite category.
