A Novel Dynamic Knowledge Extraction Method in Cooperative Multiple Robot System Using Rough Set

Hua Xu, Peifa Jia

Abstract: Dynamic knowledge extraction is one of the critical problems in dynamic systems especially in cooperative multiple robot systems (CMRS). The knowledge may be fuzzy, because the information from dynamic environments is incomplete and uncertain. So it is difficult for traditional methods to extract dynamic knowledge effectively. According to the dynamic knowledge extraction requirements in CMRS, this paper proposes a novel dynamic knowledge extraction method in CMRS on the base of KANG’s rough set based rules generation method. It has been demonstrated effective in our CMRS.