• neural network is trained with deep Q-learning in its own training environment
  • controls the game with twinject

demonstration video of the neural network playing Touhou (Imperishable Night):

it actually makes progress up to the stage boss which is fairly impressive. it performs okay in its training environment but performs poorly in an existing bullet hell game and makes a lot of mistakes.

let me know your thoughts and any questions you have!

  • 100@fedia.io
    link
    fedilink
    arrow-up
    8
    ·
    5 months ago

    one problem ive seen with these game ai projects is that you have to constantly tweak it and reset training because it eventually ends up in a loop of bad habits and doesnt progress

    so is it even possible to complete such a project with this kind of approach as it seems to take too much time to get anywhere without insane server farms?

    • zolax@programming.devOP
      link
      fedilink
      arrow-up
      3
      ·
      5 months ago

      one problem ive seen with these game ai projects is that you have to constantly tweak it and reset training because it eventually ends up in a loop of bad habits and doesnt progress

      you’re correct that this is a recurring problem with a lot of machine learning projects, but this is more a problem with some evolutionary algorithms (simulating evolution to create better-performing neural networks) where the randomness of evolution usually leads to unintended behaviour and an eventual lack of progression, while this project instead uses deep Q-learning.

      the neural network is scored based on its total distance between every bullet. so while the neural network doesn’t perform well in-game, it does actually score very good (better than me in most attempts).

      so is it even possible to complete such a project with this kind of approach as it seems to take too much time to get anywhere without insane server farms?

      the vast majority of these kind of projects - including mine - aren’t created to solve a problem. they just investigate the potential of such an algorithm as a learning experience and for others to learn off of.

      the only practical applications for this project would be to replace the “CPU” in 2 player bullet hell games and maybe to automatically gauge a game’s difficulty and programs already exist to play bullet hell games automatically so the application is quite limited.

      • 100@fedia.io
        link
        fedilink
        arrow-up
        2
        ·
        5 months ago

        i mean if you could in the future make an ai play long games from start to finish, it would be very useful to test games with thousands running at once

        • zolax@programming.devOP
          link
          fedilink
          arrow-up
          1
          ·
          5 months ago

          definitely. usually algorithms are used to calculate the difficulty of a game (eg. in osu!, a rhythm game) so there’s definitely a practical application there