Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation, explanation, and modification of knowledge about combinations of evidence, they are proposed as a tool for knowledge engineers who build systems that reason under uncertainty, not as a normative theory of evidence.
|Original language||English (US)|
|Number of pages||11|
|Journal||Artificial Intelligence for Engineering, Design, Analysis and Manufacturing|
|State||Published - Feb 1987|
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence