Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
__init__(self): self.action_space = spaces.Discrete(m+1) self.inventory = np.random.choice(np.arange(0,m+1)) self.day = np.random.choice((0,1,2,3,4,5,6)) self.state = (self.inventory, self.day) # Start the first round self.reset() def demand(self, day): if day == 0: return