DDPG¶
- class DDPG(model, gamma=None, tau=None, actor_lr=None, critic_lr=None)[源代码]¶
基类:
Algorithm
- __init__(model, gamma=None, tau=None, actor_lr=None, critic_lr=None)[源代码]¶
DDPG algorithm
- 参数:
model (parl.Model) – forward network of actor and critic.
gamma (float) – discounted factor for reward computation
tau (float) – decay coefficient when updating the weights of self.target_model with self.model
actor_lr (float) – learning rate of the actor model
critic_lr (float) – learning rate of the critic model
- learn(obs, action, reward, next_obs, terminal)[源代码]¶
Define the loss function and create an optimizer to minize the loss.
- sync_target(decay=None)[源代码]¶
update the target network with the training network
- 参数:
decay (float) – the decaying factor while updating the target network with the training network. 0 represents the assignment. None represents updating the target network slowly that depends on the hyperparameter tau.