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""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
import numpy as np | |
import cPickle as pickle | |
import gym | |
# hyperparameters | |
H = 200 # number of hidden layer neurons | |
batch_size = 10 # every how many episodes to do a param update? | |
learning_rate = 1e-4 | |
gamma = 0.99 # discount factor for reward |
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''' | |
Non-parametric computation of entropy and mutual-information | |
Adapted by G Varoquaux for code created by R Brette, itself | |
from several papers (see in the code). | |
This code is maintained at https://github.com/mutualinfo/mutual_info | |
Please download the latest code there, to have improvements and | |
bug fixes. |