Q-Learning算法（command_line_reinforcement_learning）

Q-Learning算法

import numpy as np
import pandas as pd
import time

np.random.seed(2)  # reproducible


N_STATES = 6   # the length of the 1 dimensional world
ACTIONS = ['left', 'right']     # available actions
EPSILON = 0.9   # greedy police
ALPHA = 0.1     # learning rate
GAMMA = 0.9    # discount factor
MAX_EPISODES = 13   # maximum episodes
FRESH_TIME = 0.3    # fresh time for one move


def build_q_table(n_states, actions):
    table = pd.DataFrame(
        np.zeros((n_states, len(actions))),     # q_table initial values
        columns=actions,    # actions's name
    )
    print(table)    # show table
    return table


def choose_action(state, q_table):