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272 行
5.3 KiB
272 行
5.3 KiB
default:
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trainer: sac
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batch_size: 128
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buffer_size: 50000
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buffer_init_steps: 0
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hidden_units: 128
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init_entcoef: 1.0
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learning_rate: 3.0e-4
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learning_rate_schedule: constant
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max_steps: 5.0e5
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memory_size: 128
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normalize: false
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steps_per_update: 10
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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: 10000
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tau: 0.005
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use_recurrent: false
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vis_encode_type: simple
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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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FoodCollector:
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normalize: false
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batch_size: 256
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buffer_size: 500000
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max_steps: 2.0e6
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init_entcoef: 0.05
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Bouncer:
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normalize: true
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max_steps: 1.0e6
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num_layers: 2
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hidden_units: 64
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summary_freq: 20000
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PushBlock:
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max_steps: 2e6
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init_entcoef: 0.05
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hidden_units: 256
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summary_freq: 100000
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time_horizon: 64
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num_layers: 2
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SmallWallJump:
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max_steps: 5e6
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hidden_units: 256
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summary_freq: 20000
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time_horizon: 128
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init_entcoef: 0.1
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num_layers: 2
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normalize: false
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BigWallJump:
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max_steps: 2e7
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hidden_units: 256
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summary_freq: 20000
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time_horizon: 128
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num_layers: 2
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init_entcoef: 0.1
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normalize: false
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Striker:
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max_steps: 5.0e6
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learning_rate: 1e-3
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hidden_units: 256
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summary_freq: 20000
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time_horizon: 128
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init_entcoef: 0.1
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num_layers: 2
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normalize: false
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Goalie:
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max_steps: 5.0e6
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learning_rate: 1e-3
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hidden_units: 256
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summary_freq: 20000
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time_horizon: 128
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init_entcoef: 0.1
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num_layers: 2
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normalize: false
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Pyramids:
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summary_freq: 30000
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time_horizon: 128
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batch_size: 128
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buffer_init_steps: 10000
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buffer_size: 500000
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hidden_units: 256
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num_layers: 2
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init_entcoef: 0.01
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max_steps: 1.0e7
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sequence_length: 16
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tau: 0.01
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use_recurrent: false
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reward_signals:
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extrinsic:
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strength: 2.0
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gamma: 0.99
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gail:
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strength: 0.02
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gamma: 0.99
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encoding_size: 128
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use_actions: true
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demo_path: Project/Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo
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VisualPyramids:
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time_horizon: 128
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batch_size: 64
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hidden_units: 256
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buffer_init_steps: 1000
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num_layers: 1
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max_steps: 1.0e7
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buffer_size: 500000
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init_entcoef: 0.01
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tau: 0.01
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reward_signals:
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extrinsic:
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strength: 2.0
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gamma: 0.99
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gail:
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strength: 0.02
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gamma: 0.99
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encoding_size: 128
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use_actions: true
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demo_path: Project/Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo
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3DBall:
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normalize: true
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batch_size: 64
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buffer_size: 12000
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summary_freq: 12000
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time_horizon: 1000
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hidden_units: 64
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init_entcoef: 0.5
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3DBallHard:
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normalize: true
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batch_size: 256
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summary_freq: 12000
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time_horizon: 1000
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Tennis:
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normalize: true
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max_steps: 2e7
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hidden_units: 256
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self_play:
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window: 10
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play_against_current_self_ratio: 0.5
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save_steps: 50000
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swap_steps: 50000
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CrawlerStatic:
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normalize: true
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time_horizon: 1000
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batch_size: 256
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steps_per_update: 20
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buffer_size: 500000
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buffer_init_steps: 2000
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max_steps: 3e6
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summary_freq: 30000
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init_entcoef: 1.0
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num_layers: 3
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hidden_units: 512
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.995
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CrawlerDynamic:
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normalize: true
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time_horizon: 1000
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batch_size: 256
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buffer_size: 500000
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summary_freq: 30000
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steps_per_update: 20
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num_layers: 3
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max_steps: 5e6
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hidden_units: 512
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.995
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Walker:
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normalize: true
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time_horizon: 1000
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batch_size: 256
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buffer_size: 500000
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max_steps: 2e7
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summary_freq: 30000
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num_layers: 4
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steps_per_update: 30
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hidden_units: 512
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.995
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Reacher:
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normalize: true
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time_horizon: 1000
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batch_size: 128
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buffer_size: 500000
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max_steps: 2e7
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steps_per_update: 20
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summary_freq: 60000
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Hallway:
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sequence_length: 32
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num_layers: 2
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hidden_units: 128
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memory_size: 128
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init_entcoef: 0.1
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max_steps: 5.0e6
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summary_freq: 10000
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time_horizon: 64
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use_recurrent: true
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VisualHallway:
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sequence_length: 32
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num_layers: 1
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hidden_units: 128
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memory_size: 128
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gamma: 0.99
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batch_size: 64
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max_steps: 1.0e7
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summary_freq: 10000
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time_horizon: 64
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use_recurrent: true
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VisualPushBlock:
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use_recurrent: true
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sequence_length: 32
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num_layers: 1
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hidden_units: 128
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memory_size: 128
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gamma: 0.99
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buffer_size: 1024
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batch_size: 64
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max_steps: 3.0e6
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summary_freq: 60000
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time_horizon: 64
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GridWorld:
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batch_size: 128
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normalize: false
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num_layers: 1
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hidden_units: 128
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init_entcoef: 0.5
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buffer_init_steps: 1000
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buffer_size: 50000
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max_steps: 500000
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summary_freq: 20000
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time_horizon: 5
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reward_signals:
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extrinsic:
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strength: 1.0
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gamma: 0.9
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Basic:
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batch_size: 64
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normalize: false
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num_layers: 2
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init_entcoef: 0.01
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hidden_units: 20
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max_steps: 5.0e5
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summary_freq: 2000
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time_horizon: 10
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