CIN: An Intelligent Information Management Toolkit
Grigoris Antoniou, Mary‐Anne Williams · 1996
Information systems are often faced with incomplete information, and as a consequence they have to make plausible conjectures to operate in a satisfactory way. A simple example is the Closed World Assumption which is used extensively in database systems. Default Reasoning provides formal methods which support such behaviour; the plausible conjectures are made in the absence of complete information based on default rules (“rules of thumb”). Information is subject to change due to the inherent uncertainty of information, or because the environment is volatile and dynamic. Current default reasoning systems neglect the problem raised by change. Belief Revision is the research area that has developed techniques capable of dealing with incomplete information. This paper presents the motivations, the design decisions, and the current state of the CIN Project (Changing and Incomplete information). The aim of the project is to provide an integrated toolkit for intelligent information management. We believe that providing a toolkit which is open to future enhancements is important. It is our contention that there is no “best” method for default reasoning and belief revision. Instead the system developer must seek to determine the most appropriate method for the problem at hand.