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130 行
2.8 KiB
130 行
2.8 KiB
default:
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trainer: ppo
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batch_size: 1024
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beta: 5.0e-3
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buffer_size: 10240
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epsilon: 0.2
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hidden_units: 128
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lambd: 0.95
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learning_rate: 3.0e-4
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max_steps: 5.0e4
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memory_size: 256
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normalize: false
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num_epoch: 3
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num_layers: 2
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time_horizon: 64
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sequence_length: 64
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summary_freq: 1000
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use_recurrent: false
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.99
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Pyramids:
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summary_freq: 2000
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time_horizon: 128
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batch_size: 128
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buffer_size: 2048
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hidden_units: 512
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num_layers: 2
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beta: 1.0e-2
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max_steps: 5.0e5
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num_epoch: 3
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behavioral_cloning:
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demo_path: demos/ExpertPyramid.demo
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strength: 0.5
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steps: 10000
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.99
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curiosity:
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strength: 0.02
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gamma: 0.99
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encoding_size: 256
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gail:
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strength: 0.01
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gamma: 0.99
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encoding_size: 128
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demo_path: demos/ExpertPyramid.demo
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CrawlerStatic:
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normalize: true
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num_epoch: 3
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time_horizon: 1000
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batch_size: 2024
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buffer_size: 20240
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max_steps: 1e6
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summary_freq: 3000
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num_layers: 3
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hidden_units: 512
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behavioral_cloning:
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demo_path: demos/ExpertCrawlerSta.demo
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strength: 0.5
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steps: 5000
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reward_signals:
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gail:
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strength: 1.0
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gamma: 0.99
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encoding_size: 128
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demo_path: demos/ExpertCrawlerSta.demo
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PushBlock:
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max_steps: 5.0e4
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batch_size: 128
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buffer_size: 2048
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beta: 1.0e-2
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hidden_units: 256
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summary_freq: 2000
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time_horizon: 64
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num_layers: 2
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reward_signals:
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gail:
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strength: 1.0
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gamma: 0.99
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encoding_size: 128
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demo_path: demos/ExpertPush.demo
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Hallway:
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use_recurrent: true
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sequence_length: 64
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num_layers: 2
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hidden_units: 128
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memory_size: 256
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beta: 1.0e-2
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num_epoch: 3
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buffer_size: 1024
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batch_size: 128
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max_steps: 5.0e5
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summary_freq: 1000
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time_horizon: 64
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.99
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gail:
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strength: 0.1
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gamma: 0.99
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encoding_size: 128
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demo_path: demos/ExpertHallway.demo
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FoodCollector:
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batch_size: 64
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summary_freq: 1000
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max_steps: 5.0e4
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use_recurrent: false
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hidden_units: 128
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learning_rate: 3.0e-4
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num_layers: 2
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sequence_length: 32
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reward_signals:
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gail:
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strength: 0.1
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gamma: 0.99
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encoding_size: 128
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demo_path: demos/ExpertFood.demo
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behavioral_cloning:
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demo_path: demos/ExpertFood.demo
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strength: 1.0
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steps: 0
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