👉 Reward engineering is a critical component in the field of reinforcement learning, where it involves designing and implementing reward signals to guide an agent's learning process. The primary goal is to shape the agent's behavior by providing feedback that encourages desirable actions and discourages undesirable ones, thereby accelerating learning and improving performance. This is achieved through carefully crafted reward functions that align with the desired outcomes, often incorporating both immediate and delayed feedback. By strategically structuring these rewards, engineers can influence the agent's decision-making process, making it more efficient and effective in achieving its objectives.
