parameters_q_learning Namespace Reference

Classes
class	NeuralQEstimator

Variables
list	ACTIONS = [(-0.6, 0.2), (0.6, 0.2), (0, 0.2)]
	ACTION_COUNT = len(ACTIONS)
int	LASER_SAMPLE_COUNT = 8
	MODEL_FILENAME
bool	CONTINUE = False
float	DISCOUNT_FACTOR = 0.99
int	MAX_EPISODE_LENGTH = 500
int	MEMORY_SIZE = 5000
int	BATCH_SIZE = 128
float	LEARNING_RATE = 0.0001
float	EPS_START = 1.0
float	EPS_END = 0.3
int	EPS_DECAY = 10000

Variable Documentation

parameters_q_learning.ACTION_COUNT = len(ACTIONS)

Definition at line 13 of file parameters_q_learning.py.

list parameters_q_learning.ACTIONS = [(-0.6, 0.2), (0.6, 0.2), (0, 0.2)]

Definition at line 12 of file parameters_q_learning.py.

int parameters_q_learning.BATCH_SIZE = 128

Definition at line 36 of file parameters_q_learning.py.

bool parameters_q_learning.CONTINUE = False

Definition at line 27 of file parameters_q_learning.py.

float parameters_q_learning.DISCOUNT_FACTOR = 0.99

Definition at line 29 of file parameters_q_learning.py.

int parameters_q_learning.EPS_DECAY = 10000

Definition at line 43 of file parameters_q_learning.py.

float parameters_q_learning.EPS_END = 0.3

Definition at line 42 of file parameters_q_learning.py.

float parameters_q_learning.EPS_START = 1.0

Definition at line 41 of file parameters_q_learning.py.

int parameters_q_learning.LASER_SAMPLE_COUNT = 8

Definition at line 17 of file parameters_q_learning.py.

float parameters_q_learning.LEARNING_RATE = 0.0001

Definition at line 37 of file parameters_q_learning.py.

int parameters_q_learning.MAX_EPISODE_LENGTH = 500

Definition at line 31 of file parameters_q_learning.py.

int parameters_q_learning.MEMORY_SIZE = 5000

Definition at line 34 of file parameters_q_learning.py.

parameters_q_learning.MODEL_FILENAME

Initial value:

= os.path.join(RosPack().get_path(
    "reinforcement_learning"), "q_learning.to")

Definition at line 20 of file parameters_q_learning.py.