[D] MuJoCo vs PyBullet? (esp. for custom environment)

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/reinforcementlearning

Our great sponsors
  • Scout APM - Less time debugging, more time building
  • SonarLint - Deliver Cleaner and Safer Code - Right in Your IDE of Choice!
  • SaaSHub - Software Alternatives and Reviews
  • dm_control

    DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

    If you're interested in using Mujoco, I'd suggest checking out the dm_control package for Python bindings rather than interfacing with C++ directly. I think one downside to Mujoco currently is that you cannot dynamically add objects, and the entire simulation is initialized and loaded according to the MJCF / XML file.

  • IsaacGymEnvs

    Isaac Gym Reinforcement Learning Environments

    If you already have experience in PyBullet then its probably not worth switching to Mujoco for creating custom environments. However, if you have the GPU compute for it, I'd recommend checking out Isaac Gym. GPU acceleration is great for spawning a bunch of envs for domain randomization, and it's already been used by recent research to get some great results that have previously taken a ridiculous amount of CPU compute.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts