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quadcopter.py
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quadcopter.py
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from main import *
from Environment import Environment
from shield import Shield
from DDPG import *
import argparse
def quadcopter (learning_method, number_of_rollouts, simulation_steps, learning_eposides, actor_structure, critic_structure, train_dir,\
nn_test=False, retrain_shield=False, shield_test=False, test_episodes=100):
A = np.matrix([[1,1], [0,1]])
B = np.matrix([[0],[1]])
#intial state space
s_min = np.array([[-0.5],[-0.5]])
s_max = np.array([[ 0.5],[ 0.5]])
# LQR quadratic cost per state
Q = np.matrix("1 0; 0 0")
R = np.matrix("1.0")
x_min = np.array([[-1.],[-1.]])
x_max = np.array([[ 1.],[ 1.]])
u_min = np.array([[-15.]])
u_max = np.array([[ 15.]])
env = Environment(A, B, u_min, u_max, s_min, s_max, x_min, x_max, Q, R)
args = { 'actor_lr': 0.001,
'critic_lr': 0.01,
'actor_structure': actor_structure,
'critic_structure': critic_structure,
'buffer_size': 1000000,
'gamma': 0.99,
'max_episode_len': 100,
'max_episodes': learning_eposides,
'minibatch_size': 64,
'random_seed': 6553,
'tau': 0.005,
'model_path': train_dir+"model.chkp",
'enable_test': nn_test,
'test_episodes': test_episodes,
'test_episodes_len': 5000}
actor = DDPG(env, args=args)
################# Shield ######################
model_path = os.path.split(args['model_path'])[0]+'/'
linear_func_model_name = 'K.model'
model_path = model_path+linear_func_model_name+'.npy'
shield = Shield(env, actor, model_path, force_learning=retrain_shield, debug=False)
shield.train_shield(learning_method, number_of_rollouts, simulation_steps)
if shield_test:
shield.test_shield(test_episodes, 5000, mode="single")
actor.sess.close()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Running Options')
parser.add_argument('--nn_test', action="store_true", dest="nn_test")
parser.add_argument('--retrain_shield', action="store_true", dest="retrain_shield")
parser.add_argument('--shield_test', action="store_true", dest="shield_test")
parser.add_argument('--test_episodes', action="store", dest="test_episodes", type=int)
parser_res = parser.parse_args()
nn_test = parser_res.nn_test
retrain_shield = parser_res.retrain_shield
shield_test = parser_res.shield_test
test_episodes = parser_res.test_episodes if parser_res.test_episodes is not None else 100
quadcopter ("random_search", 50, 100, 0, [240,200], [280,240,200], "ddpg_chkp/quadcopter/240200280240200/", nn_test=nn_test, retrain_shield=retrain_shield, shield_test=shield_test, test_episodes=test_episodes)