Propagation Complete Encodings of Smooth DNNF Theories

0559241 - ÚI 2023 RIV NL eng J - Journal Article
Kučera, P. - Savický, Petr
Propagation Complete Encodings of Smooth DNNF Theories.
Constraints. Roč. 27, č. 3 (2022), s. 327-359. ISSN 1383-7133. E-ISSN 1572-9354
R&D Projects: GA ČR(CZ) GA19-19463S
Institutional support: RVO:67985807
Keywords : knowledge compilation * constraint CNF encoding * DNNF * propagation complete encoding
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 1.6, year: 2022
Method of publishing: Limited access
https://dx.doi.org/10.1007/s10601-022-09331-2

We investigate conjunctive normal form (CNF) encodings of a function represented with a decomposable negation normal form (DNNF). Several encodings of DNNFs and decision diagrams were considered by (Abio et al., 2016). The authors differentiate between encodings which implement consistency or domain consistency by unit propagation from encodings which are unit refutation complete or propagation complete. The difference is that in the former case we do not care about propagation strength of the encoding with respect to the auxiliary variables while in the latter case we treat all variables (the main and the auxiliary ones) in the same way. The currently known encodings of DNNF theories implement domain consistency. Building on these encodings we generalize the result of (Abio et al., 2016) on a propagation complete encoding of decision diagrams and present a propagation complete encoding of a DNNF and its generalization for variables with finite domains.
Permanent Link: https://hdl.handle.net/11104/0332581