An Extension-Based Quotient Space Computing Model

Granular computing is not only a computing model for computer-centered problem solving, but also a thinking way for human-centered problem solving. Some authors have presented the structures of such kind models and investigated various perspectives of granular computing from different application points of views. Theory of quotient space is a new granule computing tool. In order to solve the difficult problem using theory of quotient space, the original universe of discourse space X will be turned into the new granular universe[X]. The process actually implies the idea of extenics. Extension method is mainly used to solve contradictory problems by transformations of matter-elements. So we integrate extension method with theory of quotient space to solve some complicated problems in artificial intelligence system, and set up an extension-based quotient space computing model. It provides a good scheme to find feasible approximate solutions in the problem space and realize relations and transformations between granule and granule in the whole granular worlds. And it also provides a new method for solving difficult problem. So it has great theory significance and practical value.