So I’ve been thinking about this a lot lately and it’s kind of melting my brain. Imagine we build a persistent simulated universe—like a massive physics sandbox. But instead of programming the AI with our known equations, we just drop multiple AI agents in there. We could prompt one to think like Einstein, another like Newton, etc. We give them virtual tools to measure things, a database for memory, and let them run experiments and debate each other. The goal would be for them to discover the physics of that universe purely through observation. But here is the massive catch I can’t get past: wouldn’t an advanced AI just end up reverse-engineering the simulator’s backend? Like, if the physics engine has a lag, a hardcoded limit, or a floating-point error, wouldn’t the AI just assume that glitch is a new fundamental law of nature? And how do you even stop them from “reward hacking” the simulation’s limits instead of doing actual science? I’m just a dev messing around with some side projects, but I’m super curious if any researchers are actually trying to build a multi-agent physics universe like this right now. Am I overthinking this, or is this “simulator catch-22” an actual roadblock? Would love to hear your thoughts. submitted by /u/zxpawanx
Originally posted by u/zxpawanx on r/ArtificialInteligence