Genetic Algorithms: Mario level 1-1 Completely Random Jumping.
Uploader Comments (evolsoulx)
Top Comments
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Cool project! But since the population is n = 1, this is - by definition - a hillclimbing algorithm and not a genetic a.?
All Comments (19)
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aren't you overfitting this scenario? should train other random levels, shouldn't it?
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Really cool that you got this working. If you have the source available it would be really cool if you could post a link or something
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be carefull not to get system that has learned how to pass selected map.
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@MutekiRarus the thing is: if your GA gets a good solution, the next time you try it, you may have mario failing. Becouse it is not a stable scenario, is it?
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@ernesto50 That's nonsense. Of course you can predict the moves of enemies! For example, goombas, koopas, spinies, and buzzy beetles all move forwards at a constant rate, and turn around if they hit a wall.
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very good
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you cant control or predict the moves of the enemies, so the "best" solution could not be replicated... its useless
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Liked your video. So, adjustments on random jumping are made by increasing or decreasing the frequency of the jump? or are the jumps adjusted with time and position?
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WE WANT MORE!
I dont get how its genetic if the jumping is completely random?
T3HPWN3R100 1 year ago 6
@T3HPWN3R100
This was just a test to get display's working, fitness calculations, proof that i could control it via scripting, etc.
I sadly never uploaded videos of the finished project, but it turned out pretty well. I used something like this so seed it, running it randomly for the first generation, then every generation after that was mutated/crossovered using my fitness calculations, which actually eventually got a near run.
evolsoulx 1 year ago 2