In Reinforcement Learning, the goal is to maximize long-term rewards. While the "Reward Function" provides immediate feedback for an action, the "Value Function" estimates the
"cumulative benefit" or the total expected reward an agent can gain from a particular state moving forward. For an auditor, understanding the value function is crucial because it governs the agent's long-term strategy and decision-making logic. If the value function is poorly defined, the AI might take actions that yield immediate points but lead to long-term failure or unethical shortcuts.