Comment by sodafountan
8 hours ago
This was an interesting application of AI, but I don't really think this is what LLMs excel at. Correct me if I'm wrong.
It was interesting that the poster vibe-coded (I'm assuming) the CTL from scratch; Claude was probably pretty good at doing that, and that task could likely have been completed in an afternoon.
Pairing the CTL with the CLI makes sense, as that's the only way to gain feedback from the game. Claude can't easily do spatial recognition (yet).
A project like this would entirely depend on the game being open source. I've seen some very impressive applications of AI online with closed-source games and entire algorithms dedicated to visual reasoning.
I'm still trying to figure out how this guy: https://www.youtube.com/watch?v=Doec5gxhT_U
Was able to have AI learn to play Mario Kart nearly perfectly. I find his work to be very impressive.
I guess because RCT2 is more data-driven than visually challenging, this solution works well, but having an LLM try to play a racing game sounds like it would be disastrous.
Not sure if you clocked this, but the Mario Kart AI is not an LLM. It's a randomized neural net that was trained with reinforcement learning. Apologies if I misread.
Yeah, that was the point of my post. LLMs traditionally aren't used in gaming like this.