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。
您最多选择25个主题 主题必须以中文或者字母或数字开头,可以包含连字符 (-),并且长度不得超过35个字符
 
 
 
 
 

129 行
3.1 KiB

default:
trainer: ppo
batch_size: 1024
beta: 5.0e-3
buffer_size: 10240
epsilon: 0.2
hidden_units: 128
lambd: 0.95
learning_rate: 3.0e-4
max_steps: 5.0e4
memory_size: 256
normalize: false
num_epoch: 3
num_layers: 2
time_horizon: 64
sequence_length: 64
summary_freq: 10000
use_recurrent: false
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
Pyramids:
summary_freq: 30000
time_horizon: 128
batch_size: 128
buffer_size: 2048
hidden_units: 512
num_layers: 2
beta: 1.0e-2
max_steps: 1.0e7
num_epoch: 3
behavioral_cloning:
demo_path: Project/Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo
strength: 0.5
steps: 150000
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
curiosity:
strength: 0.02
gamma: 0.99
encoding_size: 256
gail:
strength: 0.01
gamma: 0.99
encoding_size: 128
demo_path: Project/Assets/ML-Agents/Examples/Pyramids/Demos/ExpertPyramid.demo
CrawlerStatic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 1e7
summary_freq: 30000
num_layers: 3
hidden_units: 512
behavioral_cloning:
demo_path: Project/Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerSta.demo
strength: 0.5
steps: 50000
reward_signals:
gail:
strength: 1.0
gamma: 0.99
encoding_size: 128
demo_path: Project/Assets/ML-Agents/Examples/Crawler/Demos/ExpertCrawlerSta.demo
PushBlock:
max_steps: 1.5e7
batch_size: 128
buffer_size: 2048
beta: 1.0e-2
hidden_units: 256
summary_freq: 60000
time_horizon: 64
num_layers: 2
reward_signals:
gail:
strength: 1.0
gamma: 0.99
encoding_size: 128
demo_path: Project/Assets/Demonstrations/PushblockDemo.demo
Hallway:
use_recurrent: true
sequence_length: 64
num_layers: 2
hidden_units: 128
memory_size: 256
beta: 1.0e-2
num_epoch: 3
buffer_size: 1024
batch_size: 128
max_steps: 1.0e7
summary_freq: 10000
time_horizon: 64
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
gail:
strength: 0.1
gamma: 0.99
encoding_size: 128
demo_path: Project/Assets/ML-Agents/Examples/Hallway/Demos/ExpertHallway.demo
FoodCollector:
batch_size: 64
max_steps: 2.0e6
use_recurrent: false
hidden_units: 128
learning_rate: 3.0e-4
num_layers: 2
sequence_length: 32
reward_signals:
gail:
strength: 0.1
gamma: 0.99
encoding_size: 128
demo_path: Project/Assets/ML-Agents/Examples/FoodCollector/Demos/ExpertFood.demo
behavioral_cloning:
demo_path: Project/Assets/ML-Agents/Examples/FoodCollector/Demos/ExpertFood.demo
strength: 1.0
steps: 0