I don't know what it's using specifically under the hood, but in Street Fighter 6 Capcom recently added a new AI opponent you can fight that they say is trained on actual player ranked matches and fights more like a human opponent. You can even have it try to mimic your own playstyle if you've played enough.

It can do some odd things and its mimicry isn't perfect. But it definitely doesn't feel like the typical high difficulty CPU opponent which uses things like input reading to react faster than a real player ever could.

...it also has been seen teabagging.

Chess.

For most games, it's not difficult to make AI that can absolutely destroy humans. But it turns out to be very difficult to make AI that feels like a fun and engaging challenge to a human. Hardest of all is making AI that realistically plays like a human does.

The advantage of a neural AI, in my mind, isn't that it is better. It is that it is worse in a way that is fun.

Chess/Go? AlphaZero would fit that description. Also think they were tackling StarCraft as well?

Edit: https://en.m.wikipedia.org/wiki/AlphaStar_(software)

The challenge is that AI for a video game (even one fixed game) is very problem specific and there's no generalized approach/kit for developing AI for games. So while there's research showing AI can play games, it's involved lots of iteration and AI expertise. Thats obviously a large barrier for any video game and that doesn't even touch the compute requirements.

There's also the problem of making AI players fun. Too easy and they're boring, too hard and they're frustrating. Expert level AI can perform at expert level, which wouldn't be fun for the average player. Striking the right difficulty balance isn't easy or obvious.

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.

This has been discussed a lot over the decades (with some VERY good articles written by assholes we try to pretend don't exist))

The gist of it is: AI cheats because the alternative isn't "fun" and rapidly outpaces humans.

Because in an RTS? After you get a build order down, the big decider is Actions Per Minute (APM). From a build standpoint, it is the idea of triggering the appropriate research the absolute second you have enough minerals. From a combat standpoint, it is rapidly issuing move and attack orders so that you always win the combat triangle. The former isn't significantly different than just having cheaper research or faster build times. The latter is actively demoralizing in the same way that we all died inside when we first got permission to go online in Starcraft. Except at a level that even the good players realize they ain't shit.

For grand strategy games (barring real-ish time ones like Stellaris) you basically have two real approaches. The first is the games with research options (... like Stellaris. Look, I have been playing a lot of Stellaris lately). We try not to acknowledge it but RNG has a massive impact on that when you really want to get torpedoes but no options are popping so you are just doing the fastest research choices you can to get a new pool. And the difficulty option there is... a known order.

The other are the very elaborate fixed tech trees. Obviously this gets back to build order. And the reality is... the benefit gained from rapidly updating the hard mode AI to use the current meta just isn't worth it. That IS somewhere that an optimizing function can be applied to (and... semi-off-the-record but that has been a thing for over a decade and is why devs aren't THAT surprised when a "new" meta takes over in a strategy game) but it becomes a question of how much it is worth it.

All that said, we are seeing a lot more effort put into "learning" AI in racing games (driveatars) and fighting games because those tend to be cases where even the best AI is still expected to be "human" and we aren't TOO demoralized when we realize we are in a pub with Daigo. That said... there is a reason that modern SNK Bosses tend to have super armor rather than frame perfect inputs. Because the former is "bullshit" but the latter is just mean.

Didn't Alien Insurrection use something to learn how you play so the Alien knew to change it's tactics?

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.

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.

ECHO, the 3rd person action\puzzle game was a fun concept to script in your machine dopplegangers to learn on you (and repeat after you one of the set actions you can do) and reset every cycle.

I don't think it would work by itself without such limiting.

The Rain World Animation Process.
While the title suggests only animation, the AI is tied directly into the animations so you gat a 2 for 1 deal in this video.

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.

GT Sophy on Gran Turismo

Have you read about Alphastar, super computer that can whoop the best StarCraft players in the world? https://youtu.be/ZsCnuDgDcPo?feature=shared

You don't want a neural net for your game AI because it's behavior is unpredictable and therefore cannot be tested.

All of the issues AI companies have now times by a thousand because now the AI have access to a physical presence in the game world. It would cheat and find ways to know things about the game state that it's not supposed to know, or it would hide in a corner as far away from the player as possible because it's parameters is to avoid death, or some other unforeseen function of its instructions.