Reinforcement Learning, Ciencia De Dados, Data Science, Machine Learning.
alpha=0.1, gamma=1, epsilon=0.05): self.alpha = alpha #step size self.gamma = gamma #discount self.epsilon = epsilon #exploration rate for E-greedy policty assert self.gamma >0 and self.gamma <=1, "Discount factor must be between (0,1])" xr = np.arange(1,6,1) yr = np.arange(1,6,1) self.states =