import numpy as np
import gym
import random
import time
from IPython.display import clear_output
"""Creating the Environment"""
env = gym.make("FrozenLake-v0")
"""Creating the Q-Table and initializing all the Q-Values to zero for each state-action pair."""
action_space_size = env.action_space.n
state_space_size = env.observation_space …Actor(Policy)
Neural Network as Actor (Deep). vs lookup Table(Q Learning).
使用神经网络作为Actor比查表的优势？
查表无法穷举输入，e.g.图像画面或者语言输入 …