Name
Abstract | ||
|---|---|---|
We evaluate current explanation schemes. These are either insufficiently general, or suffer from other serious drawbacks. A domain-independent explanation theory, based on ignoring irrelevant variables in a probabilistic setting, is proposed. Independence-based maximum aposteriori probability (IB-MAP) explanations, an instance of irrelevance-based explanation, has several interesting properties, which provide for simple algorithms for computing such explanations. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1016/0888-613X(93)90027-B | International Journal of Approximate Reasoning |
Keywords | Field | DocType |
probabilistic reasoning,abduction,explanation under uncertainty,Bayesian belief networks,relevance | Linear system,Bayesian network,Artificial intelligence,SIMPLE algorithm,Probabilistic logic,Mathematics,Independence (probability theory),Machine learning | Journal |
Volume | Issue | ISSN |
8 | 4 | 0888-613X |
Citations | PageRank | References |
31 | 2.25 | 14 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Solomon Eyal Shimony | 1 | 687 | 78.43 |