A computational normative theory of scientific evidence

✍ Scribed by David B. Sher

• Publisher: Elsevier Science
• Year: 1992
• Tongue: English
• Weight: 909 KB
• Volume: 6
• Category: Article
• ISSN: 0888-613X
• DOI: 10.1016/0888-613x(92)90002-h

✦ Synopsis

A scientific reasoning system makes decisions using objective evidence in the form of independent experimental trials, propositional axioms, and constraints on the probabilities of events. I propose a collection of algorithms that derive probability intervals and estimate conditional probabilities from objective evidence in those forms. This reasoning system can manage uncertainty about data and rules in a rule-based expert system. I expect that the system will be particularly applicable to diagnosis and analysis in domains with a wealth of experimental evidence such as medicine. The algorithms currently apply to systems with arbitrary amounts of experimental evidence but with less than 20 variables. 1 discuss limitations of this solution and propose future directions for this research. This work can be considered a generalization of Nilsson's "'probabilistic logic" to intervals and experimental observations.