Summary

Game AI and academic AI have different objectives. Academic AI researchers try to solve real-world problems and develop AI algorithms that have to compete with human intelligence with the ultimate goal of replacing humans in complex situations. Game AI focuses on building NPCs with limited resources that seem to be intelligent to the player with the ultimate goal of entertaining the players. The objective of AI in games is to provide a challenging opponent that makes the game more fun to play. We also learned briefly about the widely used different AI techniques in games, such as FSMs, random and probability, sensor and input system, flocking and group behaviors, path following and steering behaviors, AI pathfinding, navigation mesh generation, and behavior trees. We'll see how to implement these techniques inside the Unity engine in the following chapters. In the next chapter, we will start from the very basic: Finite State Machines.