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Genetic Algorithms: Mario level 1-1 Completely Random Jumping.

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Uploaded by on Nov 19, 2009

This is just a test of fitness, seems to be working. Currently the fitness is

(Distance/MaxDistance)*100 - (time/10)

Works out pretty well, and Score can be added after the first runs of this works.

Category:

Gaming

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License:

Standard YouTube License

  • likes, 13 dislikes

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Uploader Comments (evolsoulx)

  • I dont get how its genetic if the jumping is completely random?

  • @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.

Top Comments

  • Cool project! But since the population is n = 1, this is - by definition - a hillclimbing algorithm and not a genetic a.?

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All Comments (19)

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  • aren't you overfitting this scenario? should train other random levels, shouldn't it?

  • 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

  • be carefull not to get system that has learned how to pass selected map.

  • @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?

  • @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.

  • very good

  • you cant control or predict the moves of the enemies, so the "best" solution could not be replicated... its useless

  • 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?

  • WE WANT MORE!

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