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baoblackcoal / pg-cartpole.py

Last active July 27, 2016 09:12 — forked from karpathy/pg-pong.py

Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels

	""" 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-1
	gamma = 0.99 # discount factor for reward

baoblackcoal / README

Last active June 29, 2016 01:42 — forked from JKCooper2/README

Linear Model Hill Climbing

	For part 1 of https://openai.com/requests-for-research/#cartpole

	Execute by command, for example:

	python environment.py --env CartPole-v0 --threshold 200 --noise 33
	python environment.py --env Hoodle-v0 --threshold 1 --noise 1
	(Note: Hoodle-v0 that is created by myself, and I have pulled request. https://github.com/openai/gym/pull/227 )

baoblackcoal / random_agent

Created June 12, 2016 21:41

baoblackcoal / gist:f28571bc6467bc3e94a4

Created March 29, 2016 12:32 — forked from karpathy/gist:587454dc0146a6ae21fc

An efficient, batched LSTM.

	"""
	This is a batched LSTM forward and backward pass
	"""
	import numpy as np
	import code

	class LSTM:

	@staticmethod
	def init(input_size, hidden_size, fancy_forget_bias_init = 3):

baoblackcoal / gist:0134129d24cbe02615e9

Created March 21, 2016 09:56

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