value.py 文件源码

def __init__(self, S, A, n_neighbors=5, weights='uniform', algorithm='auto', metric='minkowski', memory_fit=100, memory_size=100, **kwargs):
        #assert self.lr_mode == 'constant', 'KNNQ is only compatible with constant learning rates.'
        self.S = S
        self.A = A
        self.states = deque([])
        self.targets = deque([])
        self.memory_fit = memory_fit
        self.memory_size = memory_size
        self.count = 0

        self.neigh = KNeighborsRegressor(n_neighbors=n_neighbors, weights=weights, algorithm=algorithm, metric=metric)

        super(KNNQ, self).__init__(**kwargs)
        self.update_mode = 'set'