02_CartPole-reinforcement-learning_DDQN

PlotModel.py

pylab.figure(figsize=(18, 9))
def PlotModel(self, score, episode):
    self.scores.append(score)
    self.episodes.append(episode)
    self.average.append(sum(self.scores) / len(self.scores))
    pylab.plot(self.episodes, self.average, 'r')
    pylab.plot(self.episodes, self.scores, 'b')
    pylab.ylabel('Score', fontsize=18)
    pylab.xlabel('Steps', fontsize=18)
    dqn = 'DQN_'
    softupdate = ''
    if self.ddqn:
        dqn = 'DDQN_'
    if self.Soft_Update:
        softupdate = '_soft'
    try:
        pylab.savefig(dqn+self.env_name+softupdate+".png")
    except OSError:
        pass

    return str(self.average[-1])[:5]