mujoco VS brax

I have installed mujoco-2.3.5-window-x86_64.zip and Source Code (zip) in https://github.com/deepmind/mujoco/releases. From download file, I extracted file and clicked simulate (mujoco-2.3.5-window-x86_6 -> bin); however it shows black screen. I am not sure what I am doing wrong.

Best place for technical MuJoCo questions is our GitHub repo (https://github.com/deepmind/mujoco) -- our entire team is notified for each issue posted there.

Could you please post this question on https://github.com/deepmind/mujoco also? You'd me more likely to get an answer there since most of our team don't track Reddit questions.

Could you please post this as an issue on https://github.com/deepmind/mujoco ?

Try posting in https://github.com/deepmind/mujoco/discussions ?

Not really. You can use conda or pip to install prebuilt mujoco packages that also include glfw. Check out https://github.com/deepmind/mujoco/blob/main/python/README.md

MuJoCo Github link

There is Brax with its Ant, Humanoid and other rigid body articulated Gym environments: https://github.com/google/brax

I need differentiable rigid body dynamics because I want to do nonlinear MPC. One library that can do this is C++ is Tiny Differentiable Simulator https://github.com/erwincoumans/tiny-differentiable-simulator. As I understand it, this software uses a C++ auto-diff library and code generation to create CUDA kernels to compute fast derivatives in parallel. This seems pretty fast because it's C++. Another option is Brax https://github.com/google/brax. Brax uses JAX which I've never used, but from what I've seen online, JAX is popular for researchers and probably very good.

I am doing a MSc on robotics with a focus on machine learning, especially attention based architectures. There is a lot simulation and reinforcement learning going on. I have a funding of ~2500$ for the hardware system (no flexibility here, cannot use it for cloud either). I used pcpartpicker.com to select compatible components, as shown below. I am not located in the western part of the world; which means I have difficulty accessing some components and prices are higher here than that of pcpartpicker.com. That is why I am aiming towards 2000 - 2200$ range in the pcpartpicker.com. - Overall, what do you think of my planned setup? - Since there is a lot of simulation planned including rigid body dynamics with contact (libraries like https://github.com/raisimTech/raisimLib, https://github.com/deepmind/mujoco), I need some powerful CPU to use these libraries. I know that Intel has MKL over AMD; however, I am not sure how relevant that is for my case. The robotics simulators are generally written with C++, uses Eigen or their own math libraries. I feel like there is a lot of linear algebra involved and Intel combined with MKL should give me less headache. I have chosen i9-12900K, but what about AMD Ryzen9 5950X for example? - There is a new generation of rigid body simulators which use GPU instead of CPU (https://github.com/google/brax, https://developer.nvidia.com/isaac-gym). I do not think they are as mature as the previously mentioned simulators. Perhaps I am mistaken. Shall I focus on them instead? In terms of hardware that means I can downgrade the CPU to Ryzen5, and upgrade to RTX3080, roughly. - Do you think this system is easy to upgrade in future? What can I change to make it easier for long-term use and upgrades? Thanks for any help!

There is a new generation of rigid body simulators which use GPU instead of CPU (https://github.com/google/brax, https://developer.nvidia.com/isaac-gym). I do not think they are as mature as the previously mentioned simulators. Perhaps I am mistaken. Shall I focus on them instead? In terms of hardware that means I can downgrade the CPU to Ryzen5, and upgrade to RTX3080, roughly.

I wonder what this means for the future of Brax [1].

1. https://github.com/google/brax

If you want raw speed, parallel execution on GPU or TPU is best. Checkout out our Brax simulator, which uses the XLA compiler and JAX Python frontend: https://github.com/google/brax

Check out Brax, hardware accelerated RL training in a Google Jupyter Colab. It trains typical RL tasks in minutes on TPU, also on GPU or CPU. And it is free, you can train with just a browser: https://github.com/google/brax

Anyone made any progress with Brax? That was sold as a massively-parallel Mujoco alternative but not sure if anyone's actually using it yet.