Probabilistic Logic Programming (PLP) emerged as one of the most prominent approaches to cope with real-world domains. The distribution semantics is one of most used in PLP, as it is followed by many languages, such as Independent Choice Logic, PRISM, pD, Logic Programs with Annotated Disjunctions (LPADs) and ProbLog. A possible system that allows performing inference on LPADs is PITA, which transforms the input LPAD into a Prolog program containing calls to library predicates for handling Binary Decision Diagrams (BDDs). In particular, BDDs are used to compactly encode explanations for goals and efficiently compute their probability. However, PITA needs mode-directed tabling (also called tabling with answer subsumption), which has been implemented in SWI-Prolog only recently. This paper shows how SWI-Prolog has been extended to include correct answer subsumption and how the PITA transformation has been changed to use SWI-Prolog implementation.
Probabilistic inference in SWI-Prolog
Fabrizio Riguzzi
Primo
;Riccardo Zese
Ultimo
2018
Abstract
Probabilistic Logic Programming (PLP) emerged as one of the most prominent approaches to cope with real-world domains. The distribution semantics is one of most used in PLP, as it is followed by many languages, such as Independent Choice Logic, PRISM, pD, Logic Programs with Annotated Disjunctions (LPADs) and ProbLog. A possible system that allows performing inference on LPADs is PITA, which transforms the input LPAD into a Prolog program containing calls to library predicates for handling Binary Decision Diagrams (BDDs). In particular, BDDs are used to compactly encode explanations for goals and efficiently compute their probability. However, PITA needs mode-directed tabling (also called tabling with answer subsumption), which has been implemented in SWI-Prolog only recently. This paper shows how SWI-Prolog has been extended to include correct answer subsumption and how the PITA transformation has been changed to use SWI-Prolog implementation.File | Dimensione | Formato | |
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