👉 Reward math is a mathematical framework used to model and analyze how agents or systems learn through interactions with their environment by receiving rewards. It involves defining a reward function that quantifies the desirability of different states or actions, and then using optimization techniques, like reinforcement learning, to maximize the cumulative reward over time. This process helps agents learn optimal policies or strategies by balancing immediate rewards with long-term goals, often through methods like gradient descent to adjust actions based on the predicted outcomes of those actions.
