A Unified Framework for Nonmonotonic Reasoning with Vagueness and Uncertainty

An answer set programming paradigm is proposed that supports nonmonotonic reasoning with vague and uncertain information. The system can represent and reason with prioritized rules, rules with exceptions. An iterative method for answer set computation is proposed. The terminating conditions are identified for a class of logic programs using the notion of difference equations. In order to obtain the difference equations the set of rules are depicted by a signal-flow-graph like structure.