Comments (4)
- gym-pubulley-drones
Flythrugate
random bot VS trained agent
flythrugate_random_vs_rl.mp4
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Evogym
Carrier-v0
random bot VS trained agent
Evogym.mp4
agent during early training VS trained agent
Evogym2.mp4
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Procgen
Bigfish
random bot VS trained agent
bigfish.mp4
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Metadrive env with PPO algorithm demonstration.
Map Sequence: Straight + Intersection + Straight + Roundabout
metadrive_demonstration.mp4
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Related Issues (20)
- `dqn_rnd.py` example appears to be incorrect HOT 2
- Question about MBPO. HOT 5
- Document about config HOT 6
- wandb crash HOT 1
- Env manager is closed after wandb logger is set HOT 2
- `enable_save_figure()` has no detailed document, and its comment is wrong. HOT 4
- Does model support multiple input parameters? HOT 1
- evaluate on same env for multiple time after fails HOT 4
- `GAIL` the algorithm performs much worse than from its original paper. HOT 6
- Setting of Parameters in gym_anytrading and How to Evaluate Training Performance HOT 3
- Halfcheetah has negative state in z position HOT 2
- Error occurs when async_mode=True in example/ppo.py HOT 3
- Error occurs when running in parallel HOT 2
- NameNotFound: Environment stocks doesn't exist. HOT 11
- not compatible with gym_pybullet_drones env HOT 5
- how to use logger HOT 2
- why no tanh after sample action in ppo HOT 4
- entry_points() got an unexpected keyword argument 'group' HOT 1
- ram usage increase overtime HOT 1
- Trading deploy - issues when trying to process a single window HOT 5
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