class Actor(): def __init__(self): self.actor_estimate_eval,self.actor_reality_target = ActorNet(state_number,action_number),ActorNet(state_number,action_number) self.optimizer = torch.optim.Adam(self.actor_estimate_eval.parameters(), lr=LR_A)
时间: 2023-05-20 19:04:20 浏览: 65
这是一个 Python 中定义 Actor 类的代码,其中包含了初始化函数,该函数创建了两个 ActorNet 对象,并使用 Adam 优化器对 actor_estimate_eval 进行优化,学习率为 LR_A。这是一个深度强化学习中的 Actor-Critic 算法的实现。
相关问题
解释:self.target_actor.load_state_dict(self.actor.state_dict())
这段代码的作用是将self.actor的参数复制到self.target_actor中,这被称为Actor模型的复制,它在深度强化学习中被用来稳定学习。在深度强化学习中,有两个模型:Critic模型和Actor模型。Actor模型是基于环境反馈而生成动作的模型,而Critic模型则评估Actor选择的动作是否正确。为了避免Critic模型对Actor模型的不正确评估,需要在不同的时间点对Actor模型进行复制,以确保不同版本的Actor模型进行计算和训练。这就是这段代码的作用。
self.world.get_actor(self.car_id)
As an AI language model, I do not have enough information about the context of this code snippet to provide a complete answer. However, based on my understanding of common programming conventions, it seems like this code snippet is a method call that retrieves an actor object from a world object.
Here's a breakdown of the code snippet:
- `self.world`: This is likely an instance variable or property of an object, which represents a game world or simulation environment.
- `.get_actor()`: This is likely a method or function call on the `world` object that retrieves an actor object. It may take parameters such as an ID or name to specify which actor to retrieve.
- `self.car_id`: This is likely a variable or property of the same object that contains the ID of a car actor.
In summary, the `self.world.get_actor(self.car_id)` code snippet retrieves a car actor object from a game world or simulation environment, using the car's ID as a parameter.
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