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75 行
1.7 KiB
75 行
1.7 KiB
behaviors:
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Match3VectorObs:
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trainer_type: ppo
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hyperparameters:
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batch_size: 64
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buffer_size: 12000
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learning_rate: 0.0003
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beta: 0.001
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epsilon: 0.2
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lambd: 0.99
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num_epoch: 3
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learning_rate_schedule: constant
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network_settings:
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normalize: true
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hidden_units: 128
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num_layers: 2
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vis_encode_type: match3
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reward_signals:
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extrinsic:
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gamma: 0.99
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strength: 1.0
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keep_checkpoints: 5
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max_steps: 5000000
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time_horizon: 1000
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summary_freq: 10000
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threaded: true
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Match3VisualObs:
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trainer_type: ppo
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hyperparameters:
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batch_size: 64
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buffer_size: 12000
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learning_rate: 0.0003
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beta: 0.001
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epsilon: 0.2
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lambd: 0.99
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num_epoch: 3
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learning_rate_schedule: constant
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network_settings:
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normalize: true
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hidden_units: 128
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num_layers: 2
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vis_encode_type: match3
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reward_signals:
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extrinsic:
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gamma: 0.99
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strength: 1.0
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keep_checkpoints: 5
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max_steps: 5000000
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time_horizon: 1000
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summary_freq: 10000
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threaded: true
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Match3SimpleHeuristic:
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# Settings can be very simple since we don't care about actually training the model
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trainer_type: ppo
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hyperparameters:
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batch_size: 64
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buffer_size: 128
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network_settings:
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hidden_units: 4
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num_layers: 1
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max_steps: 5000000
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summary_freq: 10000
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threaded: true
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Match3GreedyHeuristic:
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# Settings can be very simple since we don't care about actually training the model
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trainer_type: ppo
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hyperparameters:
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batch_size: 64
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buffer_size: 128
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network_settings:
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hidden_units: 4
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num_layers: 1
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max_steps: 5000000
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summary_freq: 10000
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threaded: true
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