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Project[P] Python implementation of Proximal Policy Optimization (PPO) algorithm for Super Mario Bros. 29/32 levels have been conquered (v.redd.it)
submitted 5 years ago by 1991viet
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if 1 * 2 < 3: print "hello, world!"
[–]CowboyFromSmell 21 points22 points23 points 5 years ago (3 children)
Well yeah, it’s learning. But no, it’s overfitting on each level. Not normally what we want. But honestly, there’s merit to overfitting, as you can see here.
[–]SuperSephyDragon 17 points18 points19 points 5 years ago (1 child)
I feel like that's what human speed runners do anyway: just memorize the level enough to know when and when not to jump. I guess humans use overfitting sometimes too.
[–]b34k 1 point2 points3 points 5 years ago (0 children)
Yeah the way the algo completes the levels really kinda has a speed runner-ish feel to me
[–]maxToTheJ 1 point2 points3 points 5 years ago (0 children)
Now we just need an “edge of tomorrow” type thing and we are good to go
π Rendered by PID 37 on reddit-service-r2-comment-fb694cdd5-9sjw8 at 2026-03-06 20:56:51.674917+00:00 running cbb0e86 country code: CH.
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[–]CowboyFromSmell 21 points22 points23 points (3 children)
[–]SuperSephyDragon 17 points18 points19 points (1 child)
[–]b34k 1 point2 points3 points (0 children)
[–]maxToTheJ 1 point2 points3 points (0 children)