基于tensorflow的增强学习

可以通过下面的连接查看这个项目工程：

https://github.com/reinforceio/tensorforce

通过这遍文章来了这个项目的使用：

https://reinforce.io/blog/introduction-to-tensorforce/

from tensorforce import Configuration
from tensorforce.agents import DQNAgent
from tensorforce.core.networks import layered_network_builder

# Define a network builder from an ordered list of layers
layers = [dict(type='dense', size=32),
          dict(type='dense', size=32)]
network = layered_network_builder(layers_config=layers)

# Define a state
states = dict(shape=(10,), type='float')

# Define an action (models internally assert whether
# they support continuous and/or discrete control)
actions = dict(continuous=False, num_actions=5)

# The agent is configured with a single configuration object
agent_config = Configuration(
    batch_size=8,
    learning_rate=0.001,
    memory_capacity=800,
    first_update=80,
    repeat_update=4,
    target_update_frequency=20,
    states=states,
    actions=actions,
    network=network
)
agent = DQNAgent(config=agent_config)

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