AI Plays Super Mario Bros. 3: Playfun vs. The Sarlacc of Madness (Feat. Tom7's Learnfun & Playfun)

Welcome back to AI Plays Super Mario Bros. 3 featuring Learnfun and Playfun! In part 1, we saw how well Tom7's software can play Super Mario Bros. 3. It got to World 1-3, doing some impressive things along the way, but sadly got stuck on one rather simple obstacle. I decided to try to improve Playfun's gameplay by providing Learnfun with different training data. With the right input, can Playfun's improve and progress beyond the point where it got stuck initially?

If you haven't seen part 1, you'll want to watch that first ► https://youtu.be/IIguULLrWbw
Watch the entire series here ► https://www.youtube.com/playlist?list=PLBV81U7BXltWK9O7VnGjkd3JY36m3nR3D
All the shorts ► https://www.youtube.com/playlist?list=PLBV81U7BXltX0A8t2MGFDN5mcWip8O8kM

Learnfun and Playfun are a pair of programs that work together to (a) learn, and then (b) play any and all classic Nintendo games. They were not written specifically to play Super Mario Bros. 3 or any individual game, but rather to take a generalized approach that works with a variety of games. After receiving some training data (i.e., a recording of gameplay by a human player), Learnfun tries to determine the goals/objectives of the game. Playfun then "plays" the game, trying to maximize outcomes according to the objective data provided by Learnfun. It's an elegant system that's a marvel to watch when it gets things right...and very entertaining when it doesn't!

Want to learn more about Tom7's magic NES-playing software? You can find all the info here ► http://tom7.org/mario/
Here's Tom's YouTube channel, where he has videos of other wacky projects ► https://www.youtube.com/suckerpinch

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Video outro music: The Giddyup Kid Rap by Ashininity (uses elements licensed under Creative Commons licenses; see description at https://youtu.be/otQIT5B1h5o for attributions)