non-monotonic temporal logic

Non-monotonic temporal logic is a framework that models how our understanding of facts over time can adapt when new information appears. Unlike traditional logic, which assumes that once something is true, it remains true, non-monotonic logic allows for conclusions to be withdrawn if circumstances change. When combined with temporal aspects, it considers how facts evolve over time—embracing the reality that knowledge isn't fixed, but dynamic. This approach is useful in areas like artificial intelligence, where systems need to update beliefs as new data becomes available, reflecting real-world reasoning that is flexible and context-dependent.