17 dependents
| Package | Description | Downloads/month |
|---|---|---|
| 13K | ||
| Multi-Agent Reinforcement Learning with JAX | 6K | |
| Accelerated Quality-Diversity | 5K | |
| Cost constrained environments with a gymnax interface | 4K | |
| Collimator.ai core simulation engine and API client | 3K | |
| Interoperating between (Deep) Reiforcement Learning libraries | 855 | |
| Vectorizable RL algorithms in pure JAX | 657 | |
| a modular reinforcement learning library with JAX agents | 497 | |
| Simulation environments for basic manipulation tasks. | 345 | |
| Blazingly fast goal-conditioned environments based on MJX and BRAX. | 265 | |
| Python Boilerplate that contains all the code you need to create a Python packag... | 203 | |
| Recreating Google DeepMind's XLand RL environment in JAX | 180 | |
| Reinforcement learning in pure JAX. | 158 | |
| Interoperate among reinforcement learning libraries with jax, pytorch, gym and d... | 122 | |
| Partially Observable Benchmarks in JAX | 99 | |
| Artificial Cambrian Intelligence | 83 | |
| Synthetic gymnax environments | 72 |
