feature space in order to maximize the reward signal so one example would be AI chess or any form of AI game playing it's generally done with reinforcement learning so it's if you example if you think about the chess board the the thought I guess that's playing chess it has all of these options of the different moves they can take and the reward they're trying to maximize is winning the game and that's all that really matters and this is whether they win the game or not so it'll play this game hundreds and hundreds of times