REASONING IN QUALITATIVELY DEFINED SYSTEMS USING INTERVAL-BASED DIFFERENCE-EQUATIONS

Quantitative research and statistical techniques have long been regard ed as superior ways of analyzing knowledge in social sciences. To deal with incomplete or imprecise knowledge while modeling systems, tradit ional approaches in social sciences (i.e., management science, operati ons research) have attempted to measure social facts by making approxi mations of the problem under analysis, Recent Artificial Intelligence (AI) research on qualitative reasoning which focuses on using qualitat ive knowledge to reason about the everyday physical world, suggests an opportunity to extend the capability of current logicomathematical in struments used by social scientists, This paper proposes an interval p ropagation difference equation method, a type of qualitative-quantitat ive simulation method, to model dynamic systems by abstracting from th e underlying true model, The proposed difference equation method can b e used to model problems requiring discrete-time analysis, such as app lications involving time-lag relationships, Moreover, the method does not require the exact functional form of the problem under analysis to be known with certainty, The incomplete or imprecise knowledge availa ble about the functional form of the true model, and the values of its variables, are represented with bounding functions and interval value s respectively.