Artificial Intelligence for Creating Complex Game Character Behaviours for Simulations, Real-Time Strategy Games & More
InstructorPenny de BylInstructional delivery includes breaking down internal component pieces with clear use cases and warnings.
The curriculum follows a progression from basic NavMesh setup to complex multi-agent coordination and resource management.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
A purple retro television set displays the title Goal-Oriented Action Planning above a flowchart of action nodes such as Mix and Bake.
A stylized purple television screen displays a flowchart diagram illustrating the data flow from Actions, Goals, and World State into a Planner and FSM.
A stylized purple television frame displays a grayscale 3D hospital scene with desks and figures inside a software editor interface.
A purple retro television set displays C# code on a black screen, including Unity engine using statements and MonoBehaviour class definitions.
The implementation of the core GOAP planning system may feel brief compared to the time spent on simulation UI and environment mechanics. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
The inclusion of fundamental Unity tasks like editor navigation and basic NavMesh setup may not align with the expectations of an advanced-level course. This signal predates the displayed course update; the update may have addressed it, but the update label does not prove that it was corrected.
One signal from before the displayed update suggests that the code implementation relies on hardcoded strings and lacks robust encapsulation, which may complicate refactoring. Note that the current update label does not prove these specific coding patterns have been corrected.
The curriculum covers advanced AI techniques but includes several beginner-level Unity tasks that may not suit an advanced audience.
