Evolving an AI powered physics simulation

Say you have an Environment with a state and the way you update the environment is by sending new states to it.

Say you have an evolution system set up that can evolve neural networks which take the environment's state as input and outputs an updated environment state, which is then sent back to the environment and the environment is updated.

Now say there are objects in the environment state that, were they in the real world, would physically interact in very specific (and usually predictable) ways due to the laws of physics of our universe.

Now say you set the fitness function of the evolution system to be how closely the physical interactions in the environment model reality.

Does anyone think this would work?

Edit: as an example of how an environment could be set up, I would go with a Rube Goldberg machine. It would be fun to watch, and it's a highly specific arrangement of objects that are meant to physically interact in a specific way.