The Research on Relative Knowledge Distances and Their Cognitive Features

Abstract

Considering that existing knowledge distances fail to include cognitive differences between knowledge and correlations among cognitive standpoints of intelligent agents, this paper first explores the notion of relative knowledge distances in light of relative cognitive principles. Then, under the context of precise and fuzzy settings, this paper depicts the transformation difficulty between any two knowledge given the condition of specific knowledge, and further proves the newly owned features due to the increase of relative knowledge distances and the refinement of conditional knowledge granularities, which can well reflect progressive features of humans’ multi-granularity cognition. Meanwhile, this paper analyzes the difference between absolute knowledge and relative knowledge distances in the structural features of hierarchical clustering. At last, to model and simulate humans’ conditional cognitive features, this paper designs a feature selection algorithm based on the proposed relative knowledge distances to demonstrate the effect of cognitive standpoints and paths on different cognition such as strength, hold and weakness.