C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
jax.jit
on EnvPool (#149, @mavenlin)Note: Compared with dm_control, EnvPool can have at about 2x free speedup with only single environment setting (#139, @Trinkle23897). For the next release, we are going to use mujoco source code (#141, @Trinkle23897) to make everything faster!
Note: we are still in the progress of adding more environment from dm_control suite and box2d.
This release is for a stable version for benchmarking. We will update the benchmark result for both Atari (Pong-v5) and Mujoco (Ant-v3) soon. We observe Ant-v3 can achieve 2M+ FPS with a 192-core machine.
gym_reset_return_info
option for returning (obs, info)
in gym.Env.reset
(#97)ENVPOOL_TEST
(#93, #94)terminate_when_unhealthy
and exclude_current_positions_from_observation
for most of mujoco envs (#93)info["qpos0"]
and info["qvel0"]
in mujoco env when generating wheel (#93)We have successfully integrated Ant-v4 environment based on the newest deepmind/mujoco package! (#74) More environments are coming soon.
Other enhancement: support element-wise bound, fix classic_control action space (#67)
info["reward"]
(#50)Add toy_text (#41, #42, #43, #44, #45, #46)