Reasoning with Incomplete and Changing Information: The CIN Project

Most information systems are faced with incomplete information, even for simple database applications; therefore, they must make plausible conjectures in order to operate in a satisfactory way. A simple example is the closed world assumption, which is used extensively in the database area. Nonmonotonic reasoning (NMR) provides formal methods which support such a behavior; in default logic, for example, the plausible conjectures are based on "rules of thumb." Information is subject to change due to the inherent uncertainty of information or because the environment is volatile and dynamic. Current nonmonotonic reasoning systems neglect the problems raised by change. Belief revision (BR) is the research area that has developed techniques capable of dealing with changing information. This paper presents the motivations, the design decisions, and the current state of the CIN Project (Changing Information), whose aim is to provide an integrated toolkit of nonmonotonic reasoning and belief revision methods. The reason we design an open system is our contention that finding the right method for NMR and BR is an elusive dream, and that we should instead seek to determine the most appropriate method for the specific problem at hand.