The application of network science principles to knowledge simulation

Abstract

Current approaches to knowledge representation begin with the principles of logic and ontology that Aristotle initially introduced into history. These knowledge representation approaches focus on building systems that incorporate not only computational models, but also models that people can understand and analyze. Knowledge representation fidelity requires relationship richness of both relationship types and quantities. This paper introduces a new discipline entitled simulated knowledge. Simulated knowledge differs from knowledge representation in that simulated knowledge relaxes the requirements of human understanding while maintaining the capability for human interaction and emphasizing its computational capability. Also, instead of an Aristotelian foundation, knowledge simulation principles emphasize those of the new network science.