rewards optimization

Rewards optimization is a process used in machine learning to improve a system's performance by guiding it toward desired behaviors. It involves defining specific goals or "rewards" for the system when it takes certain actions, then adjusting those actions to maximize the overall rewards over time. Think of it like training a pet with treats: the system learns which actions lead to better outcomes and repeats those behaviors more often. This technique helps develop intelligent systems that can make better decisions in complex tasks, from game playing to autonomous vehicles, by continuously learning what leads to the best results.