Online Change

Online change, encompassing the adaptation of systems to dynamic environments and evolving data, is a burgeoning research area focusing on improving robustness and efficiency in various applications. Current efforts concentrate on developing algorithms and models, such as neural networks and self-supervised learning techniques, that enable real-time adjustments to changing conditions, including shifts in data distributions and unexpected events. This research is crucial for advancing fields like robotics, machine learning, and software engineering, where systems must effectively handle unpredictable inputs and evolving tasks to achieve reliable and adaptable performance.