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/ pg-pong.py
Last active
July 9, 2018 19:01
— forked from karpathy/pg-pong.py
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels - updated to work with Python 3.6.6
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| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import gym.spaces | |
| # 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 | |
| decay_rate = 0.99 # decay factor for RMSProp leaky sum of grad^2 |
javaswinger
/ iOS 7 Toggle.markdown
Created
June 1, 2015 19:19
— forked from anonymous/iOS 7 Toggle.markdown