Question

class A2C(model, vf_loss_coeff=None)[源代码]¶

基类：Algorithm

__init__(model, vf_loss_coeff=None)[源代码]¶

A2C algorithm

参数:

• model (parl.Model) – forward network of policy and value

• vf_loss_coeff (float) – coefficient of the value function loss

learn(obs, actions, advantages, target_values, learning_rate, entropy_coeff)[源代码]¶

参数:

• obs – An float32 tensor of shape ([B] + observation_space). E.g. [B, C, H, W] in atari.

• actions – An int64 tensor of shape [B].

• advantages – A float32 tensor of shape [B].

• target_values – A float32 tensor of shape [B].

• learning_rate – float scalar of leanring rate.

• entropy_coeff – float scalar of entropy coefficient.

predict(obs)[源代码]¶

参数:

obs – An float32 tensor of shape ([B] + observation_space). E.g. [B, C, H, W] in atari.

prob_and_value(obs)[源代码]¶

参数:

obs – An float32 tensor of shape ([B] + observation_space). E.g. [B, C, H, W] in atari.

value(obs)[源代码]¶

参数:

obs – An float32 tensor of shape ([B] + observation_space). E.g. [B, C, H, W] in atari.