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Modeling real-world social situations has proven to be one of the most daunting challenges in computational social science. With the exception of simplistic, single-domain scenarios, most computational models are quickly overwhelmed with the complexity and diversity of real-world scenarios. In this paper, we apply intent-driven modeling to a complex, real-world scenario. By mapping actors' intentions...
Uncertainty handling for semantic networks is a difficult problem which has slowed the effort to fully develop a semantic web. Uncertainty handling becomes particularly challenging when incompleteness is present in a domain, as it frequently is when modeling real-world complexity. To date, work on uncertainty frameworks for semantic networks has not intuitively captured a useful notion of uncertainty,...
Knowledge acquisition is an essential process in improving the problem-solving capabilities of existing knowledge-based systems through the absorption of new information and facilitating change in current knowledge. However, without a verification mechanism, these changes could result in violations of semantic soundness of the knowledge causing inconsistencies and ultimately, contradictions. Therefore,...
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