def __init__(self, name, globalAC, sess, conn):
self.conn = conn
self.env = GameEnv(conn=self.conn)
self.name = name
self.AC = ACNet(name, sess, globalAC)
self.sess = sess
import krpc
import time
from ksp_env import GameEnv
import math
import numpy as np
from config import ip
conn = krpc.connect(name='Tracker', ip=ip)
env = GameEnv(conn)
vessel = env.vessel
frame = vessel.orbit.body.reference_frame
vert_speed = conn.add_stream(getattr, vessel.flight(frame), 'vertical_speed')
def states():
message = ('sin',
round(
math.sin((math.radians(env.heading()))) *
(90 - env.pitch()) / 90, 2), 'cos',
round(
math.cos((math.radians(env.heading()))) *
(90 - env.pitch()) / 90, 2), 'sinr',
round(
math.sin((math.radians(env.heading() + env.roll()))) *
(90 - env.pitch()) / 90, 2), 'cosr',
round(
math.cos((math.radians(env.heading() + env.roll()))) *
(90 - env.pitch()) / 90,
2), "p", round(env.pitch(),
2), "h", round(env.heading(), 2), "r",
import numpy as np
import csv
import os
import shutil
import tensorflow as tf
import krpc
from config import OUTPUT_GRAPH, LOG_DIR, result_file, fieldnames, N_WORKERS, MAX_EP_STEP, GLOBAL_NET_SCOPE, \
UPDATE_GLOBAL_ITER, GAMMA, ENTROPY_BETA, LR_A, LR_C, conns
from ksp_env import GameEnv
print(conns)
connections = [krpc.connect(**conns[i]) for i in range(N_WORKERS)]
# connections = [krpc.connect()]
env = GameEnv(conn=connections[0])
env.reset(connections[0])
NUM_STATES = env.observation_space.shape[0]
NUM_ACTIONS = env.action_space.shape[0]
ACTION_BOUND = [env.action_space.low, env.action_space.high]
# Network for the Actor Critic
class ACNet(object):
def __init__(self, scope, sess, globalAC=None):
self.sess = sess
self.actor_optimizer = tf.train.RMSPropOptimizer(LR_A, name='RMSPropA')
self.critic_optimizer = tf.train.RMSPropOptimizer(LR_C, name='RMSPropC')
if scope == GLOBAL_NET_SCOPE:
with tf.variable_scope(scope):