Certainty-factor-like structures in Bayesian belief networks
نویسندگان
چکیده
منابع مشابه
Certainty-factor-like structures in Bayesian belief networks
The certainty-factor model was one of the most popular models for the representation and manipulation of uncertain knowledge in the early rule-based expert systems of the 1980s. After the model was criticised by researchers in arti®cial intelligence and statistics as being ad-hoc in nature, researchers and developers have stopped looking at the model. Nowadays, it is often stated that the model...
متن کاملFrom certainty factors to belief networks
The certainty-factor (CF) model is a commonly used method for managing uncertainty in rule-based systems. We review the history and mechanics of the CF model, and delineate precisely its theoretical and practical limitations. In addition, we examine the belief network, a representation that is similar to the CF model but that is grounded firmly in probability theory. We show that the belief-net...
متن کاملBelief networks / Bayesian networks
Introduction In modeling real world tasks, one inevitably has to deal with uncertainty. This uncertainty is due to the fact that many facts are unknown and or simply ignored and summarized. Suppose that one morning you find out that your grass is wet. Is it due to rain, or is it due to the sprinkler? If there is no other information, you can only talk in terms of probabilities. In a probabilist...
متن کاملProject Portfolio Risk Response Selection Using Bayesian Belief Networks
Risk identification, impact assessment, and response planning constitute three building blocks of project risk management. Correspondingly, three types of interactions could be envisioned between risks, between impacts of several risks on a portfolio component, and between several responses. While the interdependency of risks is a well-recognized issue, the other two types of interactions remai...
متن کاملCausality in Bayesian Belief Networks
We address the problem of causal interpre tation of the graphical structure of Bayesian belief networks (BBNs). We review the con cept of causality explicated in the domain of structural equations models and show that it is applicable to BBNs. In this view, which we call mechanism-based, causality is defined within models and causal asymmetries arise ·, when mechanisms are placed in the conte...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Knowledge-Based Systems
سال: 2001
ISSN: 0950-7051
DOI: 10.1016/s0950-7051(00)00073-3