ven-kyoshiro

import requests
import os
import pandas as pd
import collections
import pickle


def notify(message = 'done'):
  pass

ven-kyoshiro

import matplotlib
# matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
import gym
import numpy as np

def main():
    env = gym.make('CartPole-v0')
    env.reset()
    _ = env.render(mode='rgb_array')

ven-kyoshiro

import chainer
import chainer.functions as F
import chainer.links as L
import chainerrl
import gym
import numpy as np

# 描画用
import matplotlib as mpl
mpl.use('Agg')

ven-kyoshiro

# -*- coding:utf-8 -*-
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import scipy.optimize as optimize
from multiprocessing import Pool
import os
from tqdm import tqdm
import multiprocessing as multi

ven-kyoshiro

# -*- coding:utf-8 -*-
'''
ある人が抗体を持っている確率
p :[0-1)
想定する人数を配置する正方形の一辺
N
'''
import numpy as np
import random
import seaborn as sns

ven-kyoshiro

#
#  mnist_cnn_bn.py   date. 5/21/2016
#                    date. 6/2/2017 check TF 1.1 compatibility
#

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os

ven-kyoshiro

#!/usr/bin/env python

import gym
import numpy as np
import tensorflow as tf


class PolicyGradientAgent(object):

    def __init__(self, hparams, sess):