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AI in the game development process

The game development pipeline might vary a lot, depending on which studio you visit, but all of them lead to the creation of a video game. This is not a book about pipelines, so we won't explore them, but it's important to have a rough idea of where AI is collocated.

In fact, AI intersects with many parts of the game development pipeline. Here are some of the main ones:

  • Animation: It might surprise some of you, but there is a lot of research going on regarding this topic. Sometimes, animation and AI overlap. For instance, one of the problems that developers need to solve consists of how we can procedurally generate hundreds of animations for characters, which can behave realistically, and also how they interact with each other. In fact, solving the inverse kinematic (IK) is a mathematical problem, but which of the infinite solutions to choose to achieve a goal (or just to provide a realistic look) is an AI task. We won't face this specific problem during this book, but the last chapter will provide pointers to places where you can learn more about this.
  • Level Design: If a game automatically produces levels, then AI plays an important role in that game. Procedural Content Generation (PCG) in games is a hot topic at the moment. There are games that are entirely based on PCG. Different tools to procedurally generate height maps can help Level Designers achieve realistic looking landscapes and environments. This is indeed a wide topic to explore.
  • Game Engine: Of course, inside the game engine, there are many AI algorithms that come into play. Some of these are specific for agents, while others just improve the engine's features and/or tasks. These represent the most vast category, in which they can vary from simple algorithms to adjust a Bezier curve based on the context, to implementing behavior trees or finite state machines for animations. Under the hood, there is a lot going on here. We will explore some of these concepts in this book, but the message to take home is that an algorithm can be adapted to solve similar problems in different fields. In fact, if Finite State Machines (FSMs) are used to make decisions, why not use them to "decide" which animation to play? Or why not even handle the whole game logic (i.e. the blueprint visual scripting in Unreal Engine)?
  • Non-Player Characters (NPCs): This is the most visible example of using AI in games, and this is also the most obvious AI to the Player (we will explore more about the relationship between the AI and the player in Chapter 14, Going Beyond). This is what most of this book is focused on; that is, from moving the character (for instance, with a Pathfinding Algorithm) to making decisions (i.e. with Behavior trees), or collaborate with other NPCs (multi-agent systems).

Unfortunately, we don't have the space to deal with all of these topics in this book. Therefore, we will just be focusing on the last part (NPCs), and explore the AI Framework that's built into Unreal.

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