then the reward might be positive for reaching destination and negative forgetting to an accident maybe our agent is a robot chef and then the road might be positive for a good meal even more positive for an excellent meal and negative for making a total mess in the kitchen and the goal in reinforcement learning is for this agent to figure out through its own trial and error how to get high reward so as the human designer who gives a specification with the statement I'd like high reward and you say reward is high for the things I just described