Self-Optimizing Systems are automated systems designed to improve their performance over time without human intervention. They use algorithms and data analysis to identify inefficiencies and make adjustments, enhancing their functionality and effectiveness. These systems are commonly found in areas like machine learning, artificial intelligence, and network management. These systems continuously monitor their operations and outcomes, learning from past experiences to adapt and refine their processes. By leveraging real-time data, they can optimize resource allocation, reduce costs, and improve overall performance. Examples include smart grids and autonomous vehicles, which adjust their operations based on changing conditions.