Probability Assessments from Multiple Experts: Qualitative Information is More Robust

نویسندگان

  • Linda C. van der Gaag
  • Silja Renooij
  • Armin R. Elbers
  • Willie L. Loeffen
چکیده

For many application domains, Bayesian networks are designed in collaboration with a single expert from a single institute. Since a network is often intended for wider use, its engineering involves verifying whether it appropriately reflects expert knowledge from other institutes. Upon engineering a network intended for use across Europe, we compared the original probability assessments obtained from our Dutch expert with assessments from 38 experts in six countries. While we found large variances among the assessments per probability, very high consistency was found for the qualitative properties embedded in the series of assessments per assessor. The apparent robustness of these properties suggests the importance of capturing them in a Bayesian network under construction.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Experiences with Eliciting Probabilities from Multiple Experts

Bayesian networks are typically designed in collaboration with a single domain expert from a single institute. Since a network is often intended for wider use, its engineering involves verifying whether it appropriately reflects expert knowledge from other institutes. Upon engineering a network intended for use across Europe, we compared the original probability assessments obtained from our Du...

متن کامل

Combining the Opinions of Experts Who Partition Events Differently

This paper focuses on updating a client’s beliefs about an event based on information about the different probabilities which various experts assess for that event. A substantial literature solves this problem when all experts assess their probabilities over the same partitioning of the possible outcomes of an event. But different experts often think about the same problem in quite different wa...

متن کامل

Coherent approximation of distributed expert assessments

Expert judgments of probability and expectation play an integral role in many systems. Financial markets, public policy, medical diagnostics and more rely on the ability of informed experts (both human and machine) to make educated assessments of the likelihood of various outcomes. Experts however are not immune to errors in judgment (due to bias, quantization effects, finite information or man...

متن کامل

Two models of reliability by imprecise parameters of lifetime distributions

By analyzing the reliability of a system, it is very often assumed that all probabilities are precise, that is, that every probability involved is perfectly determinable. However, the information about reliability of components may be supplied by experts and it is difficult to expect that all experts provide precise and true reliability assessments. One of the promising tools for dealing with s...

متن کامل

Credal Networks for Military Identification

Credal networks are imprecise probabilistic graphical models generalizing Bayesian networks to convex sets of probability mass functions. This makes credal networks particularly suited to model expert knowledge under very general conditions, including states of qualitative and incomplete knowledge. In this paper, we present a credal network for risk evaluation in case of intrusion of civil airc...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010