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Uploaded my first online Game AI lecture, an introduction to procedural content generation, to YouTube. It includes a Unity example for simple constructive PCG.
I realized it would likely be wise just reply to this tweet. So here’s the second one! Search-based PCG with another Unity demo, this time for generating platformer levels.
Third lecture, this one focused on constructive PCG with a Unity demo (w/ code available) on how to generate Minecraft-like landscapes with Perlin Noise.
Fourth lecture, this one on Wave Function Collapse, a constraint-based PCG approach that uses machine learning.
Fifth lecture on the most popular machine learning approaches applied to PCG research, including two python examples. This'll be the last lecture on PCG (directly).
Sixth lecture on Deep Reinforcement Learning and why you likely shouldn't use it in game development.
Ending out this thread with my final Game AI lecture of the semester on AI-based Game Design.
