Reinforcement Learning, Ciencia De Dados, Data Science, Machine Learning.
self.alpha*( reward - self.q_values[prev_state_idx, self.prev_action] ) Realizando o experimento com o agente Q-learning: n_runs=1500 cumulative_reward = [] agent = QLearningAgent(epsilon=0.1) for run in tqdm(range(n_runs)): terminal = False k=0 r = 0 while not terminal: if k==0: response =