[klowrey]

I manage the MuJoCo.jl wrapper, and having the source code wont (naively) help with AD. Internally, there's a number of iterative algorithms that you wouldn't want to automatically differentiate, and if analytical derivatives were apparent they would be in there (the MuJoCo creator was my advisor). As it stands, finite differencing is the best way to extract derivative/gradient information from the underlying physics model of MuJoCo, and is the suggested method.

We had a paper that included MuJoCo (with custom defined adjoints) within Julia's DiffEq framework to learn continuous control policies (https://arxiv.org/abs/2012.06684) which revealed a whole host of other issues, namely that gradients are not all that helpful when your optimization landscape is insanely non-linear. But that's a different problem.

Open to chatting about; Julia is definitely the tool for this kind of work.

[ChrisRackauckas]

> namely that gradients are not all that helpful when your optimization landscape is insanely non-linear

Did you try multiple shooting? https://diffeqflux.sciml.ai/dev/examples/multiple_shooting/

I want to restructure the docs because I have come to think that any non-trivial fitting problem requires multiple shooting in order to be stable. Otherwise the loss becomes dominated by "loss values calculated beyond where the simulation has already fallen off". So I'd like to dig into some of the non-fitting examples and see if this or some other tricks are the right answer.

[plafl]

I'm not thinking just about AD. I would love lots and lots of little simulation modules instead of monolithic solutions.

Now some uninteresting story: the reason to have a look at MuJoCo is personal: I studied Mechanics I, II and Analytical Mechanics at college and thought non-continuos mechanics a solved problem. When doing my masters thesis about helicopter simulation I needed at some point to model ground contact and I thought "easy, just add a damped spring". I feel that thesis was nice for an undergrad overall but that part as you can imagine was a complete and utter piece of crap. And now at my forties I want to have vengeance.