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Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization.
Features
- GPU/TPU-accelerated physics simulations using JAX
- Fully differentiable physics engine for gradient-based learning
- Includes environments for RL benchmarks like humanoids and quadrupeds
- Supports batched parallel simulations for high efficiency
- Integrates seamlessly with reinforcement learning frameworks
Project Samples
License
Apache License V2.0Follow Brax
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