Abstract:Qualitative reasoning can predict the system behavior of complicated system with incompleted knowledge, but the combinatorial explosion of reasoning branches limits its application. Traditional algorithms not only produce intractable reasoning branches, but also occupy a lot of memory space. It makes the result of reasoning difficult to be understood, and sometimes it even leads to failure. In this paper, on the base of LSIM, a method of qualitative reasoning based on LCQR(layered causal qualitative reasoning) is proposed to solve this problem. LCQR extracts the causal relation between variables, layers it and utilizes it in qualitative reasoning. The result of LCQR is satisfying.