Esempio n. 1
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    "weight_matrix": [0, 0.006],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt":1,
    "noise_in": False,
    "noise_p": 0.002,
    #"noise_type": 1,
    "noise_type": "None",
    'time_length': 20,# 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name

exp_name.set_exp_name('DHPandDhpVI')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images',EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)
def new_dhp_vi():
    capacity= 20
    predict_round=6000
    gamma=0.6
    replay_DhpVI = ReplayBuffer(capacity=capacity)
    env_DhpVI = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
    exploration = No_Exploration()
Esempio n. 2
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penalty_para = {
    #"weight_matrix": [0, 0.002],
    "weight_matrix": [0, 0.004],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt": 1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 3,
    'time_length': 20,  # 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name
exp_name.set_exp_name('VIandHDP')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images', EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)


def new_vi():
    capacity = 2
    predict_round = 3000
    u_optim = 'sgd'
    gamma = 0.6
    replay_vi = ReplayBuffer(capacity=capacity)
    env_VI = Thickener(
        noise_p=0.03,
        noise_in=True,
Esempio n. 3
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    "weight_matrix": [0, 0.006],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt":1,
    "noise_in": False,
    "noise_p": 0.002,
    #"noise_type": 1,
    "noise_type": "None",
    'time_length': 20,# 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name

exp_name.set_exp_name('HDPandDHP')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images',EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)
def new_dhp():
    capacity= 20
    predict_round=6000
    gamma=0.0
    replay_DHP = ReplayBuffer(capacity=capacity)
    env_DHP = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
    exploration = No_Exploration()
Esempio n. 4
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penalty_para = {
    #"weight_matrix": [0, 0.002],
    "weight_matrix": [0, 0.004],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt":1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 1,
    'time_length': 20,# 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name
exp_name.set_exp_name('VIandVIub')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images',EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)
def new_vi():
    capacity=2
    predict_round=3000
    u_optim='sgd'
    gamma=0.6
    replay_vi = ReplayBuffer(capacity=capacity)
    env_VI = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
    exploration = No_Exploration()
    "weight_matrix": [0, 0.006],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt": 1,
    "noise_in": False,
    "noise_p": 0.002,
    #"noise_type": 1,
    "noise_type": "None",
    'time_length': 20,  # 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name

exp_name.set_exp_name('HDPandDhpVI')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images', EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)


def new_dhp_vi():
    capacity = 2
    predict_round = 6000
    gamma = 0.6
    replay_DhpVI = ReplayBuffer(capacity=capacity)
    env_DhpVI = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
Esempio n. 6
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    #"weight_matrix": [0, 0.002],
    #"weight_matrix": [0, 0.010],
    "weight_matrix": [0, 0.0040],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt":1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 2,
    'time_length': 20,# 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name
exp_name.set_exp_name('VIandHDPandDHP')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images',EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)
def new_vi():
    capacity=2 #经验池的大小,需要大于或等于batch_size
    predict_round=3000
    u_optim='sgd' # 寻找u*使用的梯度下降算法
    gamma=0.6
    replay_vi = ReplayBuffer(capacity=capacity)
    # 这个浓密机是用来生成数据训练预测模型用的
    env_VI = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
penalty_para = {
    #"weight_matrix": [0, 0.002],
    "weight_matrix": [0, 0.004],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt": 1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 2,
    'time_length': 20,  # 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name
exp_name.set_exp_name('Noise_HDP_actor_lr')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images', EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)


def new_hdp(Na):
    predict_round = 800
    gamma = 0.4
    replay_hdp = ReplayBuffer(capacity=2)
    env_HDP = Thickener(
        noise_p=0.01,
        noise_in=True,
    )
    exploration = No_Exploration()
Esempio n. 8
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penalty_para = {
    #"weight_matrix": [0, 0.002],
    "weight_matrix": [0, 0.004],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt": 1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 1,
    'time_length': 20,  # 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name
exp_name.set_exp_name('VIubtimes')
EXP_NAME = exp_name.get_exp_name()
img_path = os.path.join('../images', EXP_NAME)
if not os.path.exists(img_path):
    os.mkdir(img_path)


def new_vi_ub(find_times=20, find_lr=0.05):
    capacity = 2
    predict_round = 3000
    u_optim = 'SGD'
    replay_vi = ReplayBuffer(capacity=capacity)
    env_VI = Thickener(
        noise_p=0.03,
        noise_in=True,
    )
Esempio n. 9
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    #"weight_matrix": [0, 0.002],
    "weight_matrix": [0, 0.004],
    "S": [0.0001, 0.0008],
    #"S": [0.0003, 0.0024],
    #"S": [0.0000, 0.000],
}
thickner_para = {
    "dt": 1,
    "noise_in": False,
    "noise_p": 0.002,
    "noise_type": 1,
    'time_length': 20,  # 浓密机每次仿真20秒
}
from Control_Exp1001.demo.thickener.common import exp_name

exp_name.set_exp_name('HDP_actor_lr')
EXP_NAME = exp_name.get_exp_name()


def new_hdp(Na):
    predict_round = 800
    gamma = 0.4
    replay_hdp = ReplayBuffer(capacity=2)
    env_HDP = Thickener(
        noise_p=0.01,
        noise_in=True,
    )
    exploration = No_Exploration()

    print('make new hdp controller')
    hdp = HDP(