Self Optimization

Self-optimization research focuses on developing systems capable of autonomously improving their performance without external intervention. Current efforts concentrate on applying machine learning, particularly deep learning and evolutionary algorithms, within diverse frameworks like potential games, ensemble models, and Hopfield networks, to achieve this goal. These methods are being used to enhance efficiency in areas such as manufacturing processes, code generation, and network management, demonstrating significant potential for optimizing complex systems across various domains. The ultimate aim is to create more adaptable, efficient, and robust systems that can learn and improve their behavior in dynamic environments.