Have you heard the idea where you just train the model on a range of constants if your constants are off from the physical world? If the coefficient of friction changed a bit in the real world, I doubt humans would suddenly forget how to move, and instead would adjust pretty quickly. Making a model tolerant to the plausible range of sim2real errors might be possible without having an accurate simulation or hand-crafted heuristics.
Yeah, this seems like a reasonable way to train a model that controls a robot. I was addressing the verifier for mechanical designs, and I’m not sure if it’s possible to verify mechanical designs to the same level as the output of computer programs.
:) yes, we shouldn’t be sure what is possible. All we know is that currently computer programs can be verified very easily, and currently mechanical designs are verified so poorly that good designs in simulations may be useless in real life. But things are changing rapidly.
Have you heard the idea where you just train the model on a range of constants if your constants are off from the physical world? If the coefficient of friction changed a bit in the real world, I doubt humans would suddenly forget how to move, and instead would adjust pretty quickly. Making a model tolerant to the plausible range of sim2real errors might be possible without having an accurate simulation or hand-crafted heuristics.
Yeah, this seems like a reasonable way to train a model that controls a robot. I was addressing the verifier for mechanical designs, and I’m not sure if it’s possible to verify mechanical designs to the same level as the output of computer programs.
:) yes, we shouldn’t be sure what is possible. All we know is that currently computer programs can be verified very easily, and currently mechanical designs are verified so poorly that good designs in simulations may be useless in real life. But things are changing rapidly.