Tank_model.setpoint))
## Record information of state
buffer.record((Last_state, action, reward, state),
base_critic=base_critic,
base_actor=base_actor,
target_actor=target_actor,
target_critic=target_critic,
gamma=gamma,
reward=reward)
## Update base actor and base critic
base_actor, base_critic = buffer.learn(
base_critic=base_critic,
base_actor=base_actor,
target_actor=target_actor,
target_critic=target_critic,
gamma=gamma,
actor_optimizer=actor_optimizer,
critic_optimizer=critic_optimizer)
## Soft update target actor and target critic
target_actor, target_critic = update_target_single(
tau,
base_critic=base_critic,
base_actor=base_actor,
target_actor=target_actor,
target_critic=target_critic)
## Remember noise produced
Noise_mem.append(noise)
