Classes
class	QValueNetwork
	— Q-value networks More...

Functions
def	disturb (u, i)

def	onehot (ix, n=NX)

def	rendertrial (maxiter=100)

Variables
float	DECAY_RATE = 0.99

	env = DPendulum()
	— Environment More...

	feed_dict

list	h_rwd = []
	— History of search More...

float	LEARNING_RATE = 0.1

int	NEPISODES = 500
	— Hyper paramaters More...

int	NSTEPS = 50

	NU = env.nu

	NX = env.nx

	optim

	Q2 = sess.run(qvalue.qvalue,feed_dict={ qvalue.x: onehot(x2) })

	Qref = sess.run(qvalue.qvalue,feed_dict={ qvalue.x: onehot(x ) })

	qvalue = QValueNetwork()

	RANDOM_SEED = int((time.time()%10)*1000)
	— Random seed More...

	reward

float	rsum = 0.0

	sess = tf.InteractiveSession()

	u = sess.run(qvalue.u,feed_dict={ qvalue.x: onehot(x) })[0]

	x = env.reset()
	— Training More...

	x2

Detailed Description

Example of Q-table learning with a simple discretized 1-pendulum environment using a linear Q network.

Function Documentation

◆ disturb()

def qnet.disturb	(	u,
		i
	)

Definition at line 58 of file qnet.py.

◆ onehot()

def qnet.onehot	(	ix,
		n = `NX`
	)

Return a vector which is 0 everywhere except index <i> set to 1.

Definition at line 54 of file qnet.py.

◆ rendertrial()

def qnet.rendertrial ( maxiter = 100 )

Definition at line 62 of file qnet.py.

Variable Documentation

◆ DECAY_RATE

float qnet.DECAY_RATE = 0.99

Definition at line 23 of file qnet.py.

◆ env

qnet.env = DPendulum()

— Environment

Definition at line 26 of file qnet.py.

◆ feed_dict

qnet.feed_dict

Definition at line 90 of file qnet.py.

◆ h_rwd

list qnet.h_rwd = []

— History of search

Definition at line 72 of file qnet.py.

◆ LEARNING_RATE

float qnet.LEARNING_RATE = 0.1

Definition at line 22 of file qnet.py.

◆ NEPISODES

int qnet.NEPISODES = 500

— Hyper paramaters

Definition at line 20 of file qnet.py.

◆ NSTEPS

int qnet.NSTEPS = 50

Definition at line 21 of file qnet.py.

◆ NU

qnet.NU = env.nu

Definition at line 28 of file qnet.py.

◆ NX

qnet.NX = env.nx

Definition at line 27 of file qnet.py.

◆ optim

qnet.optim

Definition at line 90 of file qnet.py.

◆ Q2

qnet.Q2 = sess.run(qvalue.qvalue,feed_dict={ qvalue.x: onehot(x2) })

Definition at line 85 of file qnet.py.

◆ Qref

qnet.Qref = sess.run(qvalue.qvalue,feed_dict={ qvalue.x: onehot(x ) })

Definition at line 86 of file qnet.py.

◆ qvalue

qnet.qvalue = QValueNetwork()

Definition at line 50 of file qnet.py.

◆ RANDOM_SEED

qnet.RANDOM_SEED = int((time.time()%10)*1000)

— Random seed

Definition at line 14 of file qnet.py.

◆ reward

qnet.reward

Definition at line 82 of file qnet.py.

◆ rsum

float qnet.rsum = 0.0

Definition at line 77 of file qnet.py.

◆ sess

qnet.sess = tf.InteractiveSession()

Definition at line 51 of file qnet.py.

◆ u

def qnet.u = sess.run(qvalue.u,feed_dict={ qvalue.x: onehot(x) })[0]

Definition at line 80 of file qnet.py.

◆ x

qnet.x = env.reset()

— Training

Definition at line 76 of file qnet.py.

◆ x2

qnet.x2