Method predict

rl2/cartpole/q_learning.py:78–81

(self, s)

      self.models.append(model)

  def predict(self, s):
    X = self.feature_transformer.transform(np.atleast_2d(s))
    result = np.stack([m.predict(X) for m in self.models]).T
    return result

  def update(self, s, a, G):
    X = self.feature_transformer.transform(np.atleast_2d(s))