Name
Abstract | ||
|---|---|---|
In this paper we consider a hybrid possibilistic-probabilistic alternative approach to Probabilistic Preference Logic Networks (PPLNs). Namely, we first adopt a possibilistic model to represent the beliefs about uncertain strict preference statements, and then, by means of a pignistic probability transformation, we switch to a probabilisticbased credulous inference of new preferences for which no explicit (or transitive) information is provided. Finally, we provide a tractable approximate method to compute these probabilities. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00461-3_29 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Preferences,Possibilistic logic,Necessity degrees,Probabilistic transformation,Tractable approximation | Pignistic probability,Inference,Computer science,Preference logic,Theoretical computer science,Deductive reasoning,Artificial intelligence,Probabilistic logic,Possibilistic logic,Machine learning,Transitive relation | Conference |
Volume | ISSN | Citations |
11142 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Vanina Martinez | 1 | 259 | 26.19 |
| Lluís Godo | 2 | 888 | 56.28 |
| Gerardo I. Simari | 3 | 367 | 40.41 |