Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
self.epsilon: return np.random.choice(self.indices) if self.UCB_param is not None: UCB_estimation = self.q_estimation + \ self.UCB_param * np.sqrt(np.log(self.time + 1) / (self.action_count + 1e-5)) q_best = np.max(UCB_estimation) return np.random.choice(np.where(UCB_estimation == q_best)[0]) if