Playing complex strategy games for many years, one of the things that irks me the most is that hard AI levels often just give the dumb AI cheats to simulate it being smarter. To me, it’s not very satisfying to go against cheating AI. Are any games today leveraging neural networks to supplant or augment hand-written decision tree based AI? Are any under development? I know AI can be resource intensive, but it seems that at least turn based games could employ it.

  • linearchaos@lemmy.world
    link
    fedilink
    English
    arrow-up
    11
    arrow-down
    1
    ·
    3 days ago

    trying to live train AI against your playstyle is both expensive and unnecessary. Hard bots have never really been too much trouble. We don’t really need to use AI to outpace humans in most games. The exceptions would be an extremely long play games like chess and go.

    There’s been a lot of use in AI for platformers and stuff like trackmania, but not for competition, simply for speedruns.

    • Encrypt-Keeper@lemmy.world
      link
      fedilink
      English
      arrow-up
      2
      ·
      2 days ago

      Hard bots have actually been so much trouble, that literally the only way to make them hard at all is to make them cheat by allowing them to operate outside of the ruleset the player is bound by. It’s a humongous issue with every strategy game on the market.

    • acosmichippo@lemmy.world
      link
      fedilink
      English
      arrow-up
      4
      ·
      edit-2
      2 days ago

      yeah I would like to leverage AI for stuff like RPG NPCs. instead of hearing the same filler lines for 200 hours of gameplay, barely reacting to the context of your game you could have a vibrant array of endless dialog that actually keeps up with your game progress (or lack thereof).

    • ampersandrew@lemmy.world
      link
      fedilink
      English
      arrow-up
      3
      ·
      3 days ago

      It would certainly be nice to have for the fighting games I play. A few have toyed with the idea of “shadow fighters”, but it never really feels like playing against a person. It might get their habits down, but it doesn’t replicate the adaptation of facing a person and having them change how they play based on how you’re playing. If someone could crack that nut, everyone would have someone on their level to play against at any hour of the day, no matter how obscure the game is.

  • Katana314@lemmy.world
    link
    fedilink
    English
    arrow-up
    2
    ·
    2 days ago

    The most advanced AI I’ve seen is in Hitman WoA, and Zelda: Breath of the Wild.

    Both games don’t have “learning” AI. They just have tons of rules that the player can reasonably expect and interact with, that make them seem lifelike. If a guard sees you throw a coin twice in Hitman, he doesn’t get suspicious and investigate - he goes and picks it up just like the first one. Same for reactions to finding guns, briefcases, or your exploding rubber duck.

      • count_dongulus@lemmy.worldOP
        link
        fedilink
        English
        arrow-up
        2
        ·
        3 days ago

        Oh that’s really interesting; I hadn’t considered racing games as a genre to benefit from this type of machine learning. I guess I figured there’s not so much to AI there that it’s necessary, at least when we already know the “ideal lap line” for cars to follow, but yeah it gets a lot harder when considering other drivers on the track and a huge array of unique car models with their own handling and performance characteristics.

        • drspod@lemmy.ml
          link
          fedilink
          English
          arrow-up
          4
          ·
          3 days ago

          I played Forza Horizon 4 and the Drivatars are pretty convincing. They make exactly the kind of mistakes on the track that I make and they can be challenging but beatable in a way that’s much more fun than any other racing game I had played before.

  • szczuroarturo@programming.dev
    link
    fedilink
    English
    arrow-up
    2
    arrow-down
    1
    ·
    2 days ago

    Im pretty sure we could make AI in games smarter and/or better than humans for a long time. They are just not fun to play against. You need to have AI that you can win against. What i think should be happening instead of neural networks is the ai should gamble a bit more . The good example is eu4 where on hard difficulty ai will not attack you until its sure it can win… which makes it more predictable than normal ai beacuse you can reasonably guess whetewer it will attack you and try to outmanouver it. Wheras on normal sometimes it will just attack you if there is a reasonable ( or sometimes even unreasonable ) chance to win which makes normal sometimes( very very very very rarely ) harder difficulty. Now hard difficulty is stil generaly ( 99,9% of time ) much harder due to ai cheats but what i said is a thing. Total war Warhammer 3 could use that in particular to spice things up. Currently attacking army will always attack and defending will defend which makes attacking more advantagous , and the army will always wait for reinforcment . They could for example make it so depending on the army composition ( or even just rng ) the defending army will sometimes attack ( for example when there are only melee combatants ) so that you dont have time to deal damage with mage . Or the opposite. Make it so the attacking army will just stay still and protect the artilery and bombard you with canons it it has lots of artilery . Like you know just some basic strategies so the fights arent always so similar at the begining.

    • Ephera@lemmy.ml
      link
      fedilink
      English
      arrow-up
      2
      ·
      1 day ago

      Yeah, the easiest thing to implement is omnipotent AI. The code for the AI is executed within the game engine, so you have complete access to any information you want.

      You can just query the player position at any point in time, even if there’s a wall between the NPC and the player. It requires extra logic to not use the player position in such a case, or to only use the rough player position after the player made a noise, for example.

      Of course, the decision-making is a whole separate story. Even an omnipotent AI won’t know how to use this information, unless you provide it with rules.

      I’m guessing, what OP wants is:

      1. limiting the knowledge of the AI by just feeding it a rendered image like humans see it, and
      2. somehow train AI on this input, so it figures out such rules on its own.
  • irotsoma@lemmy.world
    link
    fedilink
    English
    arrow-up
    2
    ·
    2 days ago

    The only issue with current systems is that the “AI” is tweaked to the specific game mechanics. You can easily enough build multiple algorithms for varying play styles and then have it adapt to counter the play style of the player. The problems is that the current way that many games are monetized is through expansions, gameplay tweaks, etc., as well as those being necessary when a game mechanic turns out to be really poorly implemented or just unpopular and the mechanics change. If the “AI” isn’t modified at the same time to rake advantage of the changes, then it becomes easy to beat. The other issue is that eventually a human can learn all of the play style algorithms and learn to counter them and then it becomes boring.

    Unfortunately, generative “AI” is not a true learning model and thus not truly intelligent in any sense of the word. It requires that it is only “taught” with good information. So if it gets any data that includes even slight mistakes, it can end up making lots of those mistakes repeatedly. And if those mistakes aren’t corrected by a human, it doesn’t understand which things were mistakes and how they contributed to winning or losing. It can’t learn that they were mistakes or to not do them. It doesn’t truly understand how to decide something is wrong on its own, only that things are related and how often it should use those relationships over others. Which means manual training is required, which due to the sheer volume of information required to train a generative “AI”, is not possible in a complex game where the player has thousand of possible moves that each branch to thousands of possible combinations of moves, etc.