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SpaceInvadersNoFrameskip-v4

Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
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  1. .gitattributes +28 -35
  2. README.md +59 -1
  3. args.yml +59 -0
  4. config.yml +13 -0
  5. env_kwargs.yml +1 -0
  6. qrdqn-SpaceInvadersNoFrameskip-v4.zip +3 -0
  7. replay.mp4 +3 -0
  8. results.json +1 -0
  9. train_eval_metrics.zip +3 -0
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README.md CHANGED
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  ---
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- license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ library_name: stable-baselines3
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+ tags:
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+ - SpaceInvadersNoFrameskip-v4
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+ - deep-reinforcement-learning
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+ - reinforcement-learning
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+ - stable-baselines3
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+ model-index:
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+ - name: QRDQN
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+ results:
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+ - metrics:
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+ - type: mean_reward
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+ value: 2169.00 +/- 1108.30
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+ name: mean_reward
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+ task:
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+ type: reinforcement-learning
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+ name: reinforcement-learning
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+ dataset:
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+ name: SpaceInvadersNoFrameskip-v4
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+ type: SpaceInvadersNoFrameskip-v4
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  ---
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+
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+ # **QRDQN** Agent playing **SpaceInvadersNoFrameskip-v4**
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+ This is a trained model of a **QRDQN** agent playing **SpaceInvadersNoFrameskip-v4**
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+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
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+ and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
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+
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+ The RL Zoo is a training framework for Stable Baselines3
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+ reinforcement learning agents,
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+ with hyperparameter optimization and pre-trained agents included.
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+
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+ ## Usage (with SB3 RL Zoo)
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+
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+ RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
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+ SB3: https://github.com/DLR-RM/stable-baselines3<br/>
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+ SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
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+
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+ ```
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+ # Download model and save it into the logs/ folder
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+ python -m rl_zoo3.load_from_hub --algo qrdqn --env SpaceInvadersNoFrameskip-v4 -orga sb3 -f logs/
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+ python enjoy.py --algo qrdqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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+ ```
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+
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+ ## Training (with the RL Zoo)
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+ ```
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+ python train.py --algo qrdqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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+ # Upload the model and generate video (when possible)
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+ python -m rl_zoo3.push_to_hub --algo qrdqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga sb3
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+ ```
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+
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+ ## Hyperparameters
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+ ```python
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+ OrderedDict([('env_wrapper',
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+ ['stable_baselines3.common.atari_wrappers.AtariWrapper']),
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+ ('exploration_fraction', 0.025),
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+ ('frame_stack', 4),
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+ ('n_timesteps', 10000000.0),
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+ ('optimize_memory_usage', True),
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+ ('policy', 'CnnPolicy'),
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+ ('normalize', False)])
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+ ```
args.yml ADDED
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+ !!python/object/apply:collections.OrderedDict
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+ - - - algo
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+ - qrdqn
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+ - - env
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+ - SpaceInvadersNoFrameskip-v4
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+ - - env_kwargs
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+ - null
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+ - - eval_episodes
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+ - 10
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+ - - eval_freq
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+ - 10000
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+ - - gym_packages
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+ - []
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+ - - hyperparams
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+ - null
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+ - - log_folder
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+ - rl-trained-agents/
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+ - - log_interval
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+ - -1
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+ - - n_evaluations
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+ - 20
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+ - - n_jobs
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+ - 1
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+ - - n_startup_trials
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+ - 10
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+ - - n_timesteps
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+ - -1
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+ - - n_trials
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+ - 10
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+ - - num_threads
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+ - -1
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+ - - optimize_hyperparameters
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+ - false
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+ - - pruner
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+ - median
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+ - - sampler
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+ - tpe
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+ - - save_freq
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+ - -1
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+ - - save_replay_buffer
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+ - false
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+ - - seed
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+ - 403688348
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+ - - storage
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+ - null
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+ - - study_name
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+ - null
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+ - - tensorboard_log
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+ - ''
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+ - - trained_agent
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+ - ''
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+ - - truncate_last_trajectory
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+ - true
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+ - - uuid
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+ - true
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+ - - vec_env
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+ - dummy
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+ - - verbose
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+ - 1
config.yml ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ - - - env_wrapper
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+ - - stable_baselines3.common.atari_wrappers.AtariWrapper
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+ - - exploration_fraction
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+ - 0.025
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+ - - frame_stack
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+ - 4
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+ - - n_timesteps
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+ - 10000000.0
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+ - - optimize_memory_usage
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+ - true
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+ - - policy
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+ - CnnPolicy
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