The Goal Oriented Action Planner (GOAP) is an AI architecture that simplifies the process of building complex Finite State Machines (FSMs) by allowing you to define goals and actions, and automatically figuring out which actions to take to achieve those goals.
GOAP can help you build complex AI by defining simple actions which GOAP connects together. It also resolves the best action to take based on the game state, making managing a complex decision graph much easier.
Key features include a multithreaded resolver, a visualizer window, and support for data injection using your favorite IoC. The core is well-documented and unit tested.
The GOAP resolver is multithreaded, using jobs for efficient processing. It also includes a setup method using ScriptableObject configuration in the editor, or by using code. Two example scenes are provided, demonstrating both setup methods. Additionally, the core is unit tested and well-documented.
