Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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behaviors:
CrawlerStatic:
trainer_type: sac_transfer
hyperparameters:
learning_rate: 0.0003
learning_rate_schedule: linear
model_schedule: constant
batch_size: 256
buffer_size: 3000000
buffer_init_steps: 2000
tau: 0.005
steps_per_update: 20.0
save_replay_buffer: false
init_entcoef: 1.0
reward_signal_steps_per_update: 20.0
encoder_layers: 2
policy_layers: 1
forward_layers: 1
value_layers: 2
feature_size: 128
separate_policy_train: true
separate_model_train: true
# separate_value_net: true
reuse_encoder: true
in_epoch_alter: false
in_batch_alter: true
use_op_buffer: false
use_var_predict: true
with_prior: false
predict_return: true
network_settings:
normalize: true
hidden_units: 512
num_layers: 3
vis_encode_type: simple
reward_signals:
extrinsic:
gamma: 0.995
strength: 1.0
keep_checkpoints: 5
max_steps: 3000000
time_horizon: 1000
summary_freq: 30000
threaded: true