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These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
from concurrent.futures import ProcessPoolExecutor, as_completed | |
import cv2 | |
import multiprocessing | |
import os | |
import sys | |
def print_progress(iteration, total, prefix='', suffix='', decimals=3, bar_length=100): | |
""" | |
Call in a loop to create standard out progress bar |
# Inspired by https://medium.com/@tuzzer/cart-pole-balancing-with-q-learning-b54c6068d947 | |
import gym | |
import numpy as np | |
import math | |
from collections import deque | |
class QCartPoleSolver(): | |
def __init__(self, buckets=(1, 1, 6, 12,), n_episodes=1000, n_win_ticks=195, min_alpha=0.1, min_epsilon=0.1, gamma=1.0, ada_divisor=25, max_env_steps=None, quiet=False, monitor=False): | |
self.buckets = buckets # down-scaling feature space to discrete range |