Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
and updates estimations based on the reward. The update process depends on the chosen algorithm. # take an action, update estimation for this action def step(self, action): # generate the reward under N(real reward, 1) reward = np.random.randn() + self.q_true[action] self.time += 1