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Comment by cachius | Hacker News Reader

This is what StuffMadeHere used in his latest video to simulate a mini-golf course! https://www.youtube.com/watch?v=2OfjZ3ORJfc&t=368s

The physics engine I'm using is called MuJoCo. And if you're wondering why I didn't write my own physics engine, it's basically because I don't have 20 years.

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It's what put MuJoCo on my radar recently! But I was surprised to not see him do any kind of gradient descent to optimize his hyperparameters. MuJoCo has a JAX backend so it should be fairly straightforward.

He is much better at building hardware than he is writing software.

He seems pretty damn good at both.

I'm pretty sure he has used gradient descent in previous videos to optimize systems, maybe this time it was just easier to hand tune rather than set up an optimization feedback harness around MuJoCo.

That the calibration got the simulation so close to reality was quite impressive.

Though he had to resort to manual calibration. I always find he has interesting problems for domain experts and would like to see him team up with one. Also with programmers for faster programs than self taught python.

The guy has a masters in compsci and mechanical engineering, he has done both python and c++ afaik for his projects

I think the parent comment is specifically addressing why the black box (or stochastic?) optimizer he used not working.

In the video in question, he doesn't seem able to choose a good scoring function for the stochastic solver (even over multiple weeks), seemingly choosing a linear sum of distances (see 8:50) between simulation and reality. That's a mistake that not even an undergraduate should make. He needs some domain experts.

I did comp sci, I sucked at this stuff, and I have a masters.

Low level stuff? Os? Distributed systems? Multithreaded code? Now that’s more on my alley

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