A tool for ramification reasoning over temporal OWL knowledge bases

In this paper we study the ramification problem in the setting of time-owl. Standard solutions from the literature on reasoning about action are inadequate because they rely on the assumption that fluents persist, and actions have effects on the next situation only. In this paper we provide a solution to the ramification problem based on an extension of the situation calculus and the work of McCain and Turner. In our approach lies the use of static and dynamic rules which capture the indirect and direct effects of actions. Also our tool has the ability to address the frame problem which refers to the identification of fluents that remain unchanged as result of actions.