MujocoUnity
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Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).
MujocoUnity
Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).
Presented March 19th, 2018 at the AI Summit - Game Developer Conference 2018 - http://schedule.gdconf.com/session/beyond-bots-making-machine-learning-accessible-and-useful/856147
IMPORTANT: Active development has moved to Marathon-envs
- This project is now a add-on for Unity ML-Agents Toolkit and is still being maintained and supported. See the new repro here - https://github.com/Unity-Technologies/marathon-envs

Legacy readme...
v0.2
supports Unity ml-agents (instructions)
Trained with ml-agents PPO:
unity_oai_hopper.xml
1.5m steps
unity_dm_walker.xml
3m steps
Trained with Baselines DDPG:
unity_oai_hopper.xml
300k steps
2m steps
unity_dm_walker.xml
1m steps
3m steps
Note: to reproduce you'll need to figure out how to patch OpenAI baselines with Unity.
Known Issues:
- oai_humanoid - is broken. Configurable joint needs updating to support multi-directional joints
- oai_half_cheetah - need to implement geom axis-angle
- dm_xxxx - need to implement class=
- phyx is not tuned properly
- Capsules are slightly too long - NOTE: this can cause collision issues whereby the leg may slightly poke the a foot and trigger collisions
From earlier version:
Ant - Random
Ant - trained with ACKTR 