© 2016, CEUR-WS. All rights reserved. A flexible semantics has been proposed by Lukasiewicz for probabilistic logic programs where we have a normal logic program augmented with a set of independent probabilistic facts. That semantics, which we call credal semantics, is the set of all probability measures (over stable models) that are consistent with a total choice of probabilistic facts. When each total choice produces a definite program, credal semantics is identical to Sato's distribution semantics. However, credal semantics is also defined for programs with cycles and negations. We show that the credal semantics always defines a set containing the probability measures that dominate an infinite monotone Choquet capacity (also known as a belief function). We also show how this result leads to inference algorithms and to an analysis of the complexity of inferences.
|Original language||American English|
|Number of pages||12|
|State||Published - 1 Jan 2016|
|Event||CEUR Workshop Proceedings - |
Duration: 1 Jan 2016 → …
|Conference||CEUR Workshop Proceedings|
|Period||1/01/16 → …|