another action in response to that and the environments going to give you back another reward and the next observation and so on so what you want to do is you want to find a mapping from observation to action such that your reward is going to be as high as possible right this is the fundamental problem of RL and usually what people do is they take this act this mapping here from observation to action to be some sort of function some sort of function that is parameterised maybe and nowadays of course it's often a neural network but