def __init__(self, state_size, action_size, seed):
    'Initialize an Agent object.\n        \n        Params\n        ======\n            state_size (int): dimension of each state\n            action_size (int): dimension of each action\n            seed (int): random seed\n        '
    self.state_size = state_size
    self.action_size = action_size
    self.seed = random.seed(seed)
    self.qnetwork_local = QNetwork(state_size, action_size, seed).to(device)
    self.qnetwork_target = QNetwork(state_size, action_size, seed).to(device)
    self.optimizer = optim.Adam(self.qnetwork_local.parameters(), lr=LR)
    self.memory = ReplayBuffer(action_size, BUFFER_SIZE, BATCH_SIZE, seed)
    self.t_step = 0
Initialize an Agent object.

Params
======
    state_size (int): dimension of each state
    action_size (int): dimension of each action
    seed (int): random seed
def __init__(self, state_size, action_size, seed):
    'Initialize an Agent object.\n        \n        Params\n        ======\n            state_size (int): dimension of each state\n            action_size (int): dimension of each action\n            seed (int): random seed\n        '
    self.state_size = state_size
    self.action_size = action_size
    self.seed = random.seed(seed)
    self.qnetwork_local = QNetwork(state_size, action_size, seed).to(device)
    self.qnetwork_target = QNetwork(state_size, action_size, seed).to(device)
    self.optimizer = optim.Adam(self.qnetwork_local.parameters(), lr=LR)
    self.memory = ReplayBuffer(action_size, BUFFER_SIZE, BATCH_SIZE, seed)
    self.t_step = 0