(self, s, a, G, gamma, lambda_)
| 61 | return result |
| 62 | |
| 63 | def update(self, s, a, G, gamma, lambda_): |
| 64 | X = self.feature_transformer.transform([s]) |
| 65 | assert(len(X.shape) == 2) |
| 66 | self.eligibilities *= gamma*lambda_ |
| 67 | self.eligibilities[a] += X[0] |
| 68 | self.models[a].partial_fit(X[0], G, self.eligibilities[a]) |
| 69 | |
| 70 | def sample_action(self, s, eps): |
| 71 | if np.random.random() < eps: |
no test coverage detected