A Methodology for Uncertainty in Knowledge-Based Systems /
Weichselberger, Kurt, 1929-
A Methodology for Uncertainty in Knowledge-Based Systems / by Kurt Weichselberger, Sigrid Pöhlmann. - Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. - 1 online resource (VIII, 132 pages) - Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 419 0302-9743 ; . - Lecture notes in computer science. Lecture notes in artificial intelligence ; 419. .
Includes bibliographical references.
The aims of this study -- Interval estimation of probabilities -- Related theories -- The simplest case of a diagnostic system -- Generalizations -- Interval estimation of probabilities in diagnostic systems -- A demonstration of the use of interval estimation.
In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.
9783540469643 3540469648
10.1007/BFb0037513 doi
Computer science.
Artificial intelligence.
Distribution (Probability theory)
Statistics.
Electronic data processing.
Informatique.
Intelligence artificielle.
Distribution (Théorie des probabilités)
Statistique.
computer science.
data processing.
artificial intelligence.
distribution (statistics-related concept)
statistics.
Electronic data processing
Artificial intelligence
Computer science
Distribution (Probability theory)
Statistics
QA76.76.E95 / W44 1990 TJ210.2-211.495
006.3
A Methodology for Uncertainty in Knowledge-Based Systems / by Kurt Weichselberger, Sigrid Pöhlmann. - Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. - 1 online resource (VIII, 132 pages) - Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 419 0302-9743 ; . - Lecture notes in computer science. Lecture notes in artificial intelligence ; 419. .
Includes bibliographical references.
The aims of this study -- Interval estimation of probabilities -- Related theories -- The simplest case of a diagnostic system -- Generalizations -- Interval estimation of probabilities in diagnostic systems -- A demonstration of the use of interval estimation.
In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.
9783540469643 3540469648
10.1007/BFb0037513 doi
Computer science.
Artificial intelligence.
Distribution (Probability theory)
Statistics.
Electronic data processing.
Informatique.
Intelligence artificielle.
Distribution (Théorie des probabilités)
Statistique.
computer science.
data processing.
artificial intelligence.
distribution (statistics-related concept)
statistics.
Electronic data processing
Artificial intelligence
Computer science
Distribution (Probability theory)
Statistics
QA76.76.E95 / W44 1990 TJ210.2-211.495
006.3