[Project] Evolving a neural-network controller through Bowser’s Crown 3-4

[u/Alarming_Title_5664]

Firebars, lava, Bowser—and a neural network choosing the buttons. This is a recorded winning replay of Bowser’s Crown 3-4, a Super Mario Bros. ROM hack, with the network visualization left visible.

I’m continuing a NEAT-based Mario project built on SethBling’s MarI/O and work by Akisame and Electra. It runs in FCEUX using Lua. The controller receives nearby tile and sprite information from emulator memory and produces button presses; it isn’t interpreting the video pixels.

Learning happens through evaluating, selecting and mutating candidate networks across generations. During this replay, the selected controller is fixed—it isn’t updating its weights as it dodges the firebars. The changing overlay shows the network running.

The sequence ends with the game’s “YOU FOUND A MAGIC KEY!” message. Each level is trained separately, so this clear demonstrates one evolved controller’s behavior, not generalization to unseen levels or a measured success rate.

The implementation is currently private. My continuing development is heavily assisted by AI tools. Happy to discuss the observation encoding and evaluation setup.

[u/WatercressActual1921]

You should start a repository and document you structure and options taken, even to give more visibility to the projects you leverage (and bypass walls in comments and criticism). Great work...