Reinforcement Learning, Ciencia De Dados, Data Science, Machine Learning.
[x*10 + y for x in xr for y in yr] self.smap = dict(enumerate(states)) self.smap = {v:k for k,v in self.smap.items()} #mapeia os estados recebidos nas linhas da matriz q self.actions = [0, 1, 2, 3] self.q_values = np.zeros((len(self.states), len(self.actions))) def policy(self): if