Causal Networks and Their Decomposition Theories
Zhiqiang Liu · 2002
Causal networks (CNs) have been used to construct inference systems for diagnostics and decision making. More recently, Bayesian causal networks (BCNs) and fuzzy causal networks (FCNs) have gained considerable attention and offer an alternative framework for representing structured human knowledge and are used in causal inference in many real-world applications. However, for large systems, it is difficult to analyze and design causal networks. This paper presents two new approaches to partitioning fuzzy causal networks: causal modules and quotient space.