Hybrid Probabilistic Programs

dc.contributor.authorDekhtyar, Alexen_US
dc.contributor.authorSubrahmanian, V. S.en_US
dc.date.accessioned2004-05-31T22:50:34Z
dc.date.available2004-05-31T22:50:34Z
dc.date.created1998-03en_US
dc.date.issued1998-10-15en_US
dc.description.abstractThe precise probability of a compound event (e.g. e1 v e2, e1 ^ e2) depends upon the known relationships (e.g. independence, mutual exclusion, ignorance of any relationship, etc.) between the primitive events that constitute the compound event. To date, most research on probabilistic logic programming [20, 19, 22, 23, 24] has assumed that we are ignorant of the relationship between primitive events. Likewise, most research in AI (e.g. Bayesian approaches) have assumed that primitive events are independent. In this paper, we propose a hybrid probabilistic logic programming language in which the user can explicitly associate, with any given probabilistic strategy, a conjunction and disjunction operator, and then write programs using these operators. We describe the syntax of hybrid probabilistic programs, and develop a model theory and fixpoint theory for such programs. Last, but not least, we develop three alternative procedures to answer queries, each of which is guaranteed to be sound and complete. (Also cross-referenced as UMIACS-TR-98-16)en_US
dc.format.extent469405 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/944
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3883en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-98-16en_US
dc.titleHybrid Probabilistic Programsen_US
dc.typeTechnical Reporten_US

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