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:
BigWallJump:
trainer_type: ppo
hyperparameters:
batch_size: 128
buffer_size: 2048
learning_rate: 0.0003
beta: 0.005
epsilon: 0.2
lambd: 0.95
num_epoch: 3
learning_rate_schedule: linear
network_settings:
normalize: false
hidden_units: 256
num_layers: 2
vis_encode_type: simple
reward_signals:
extrinsic:
gamma: 0.99
strength: 1.0
output_path: default
keep_checkpoints: 5
max_steps: 20000000
time_horizon: 128
summary_freq: 20000
threaded: true
SmallWallJump:
trainer_type: ppo
hyperparameters:
batch_size: 128
buffer_size: 2048
learning_rate: 0.0003
beta: 0.005
epsilon: 0.2
lambd: 0.95
num_epoch: 3
learning_rate_schedule: linear
network_settings:
normalize: false
hidden_units: 256
num_layers: 2
vis_encode_type: simple
reward_signals:
extrinsic:
gamma: 0.99
strength: 1.0
output_path: default
keep_checkpoints: 5
max_steps: 5000000
time_horizon: 128
summary_freq: 20000
threaded: true
curriculum:
BigWallJump:
measure: progress
thresholds: [0.1, 0.3, 0.5]
min_lesson_length: 100
signal_smoothing: true
parameters:
big_wall_min_height: [0.0, 4.0, 6.0, 8.0]
big_wall_max_height: [4.0, 7.0, 8.0, 8.0]
SmallWallJump:
measure: progress
thresholds: [0.1, 0.3, 0.5]
min_lesson_length: 100
signal_smoothing: true
parameters:
small_wall_height: [1.5, 2.0, 2.5, 4.0]