English

Belief Revision in Sentential Decision Diagrams

Artificial Intelligence 2022-01-21 v1

Abstract

Belief revision is the task of modifying a knowledge base when new information becomes available, while also respecting a number of desirable properties. Classical belief revision schemes have been already specialised to \emph{binary decision diagrams} (BDDs), the classical formalism to compactly represent propositional knowledge. These results also apply to \emph{ordered} BDDs (OBDDs), a special class of BDDs, designed to guarantee canonicity. Yet, those revisions cannot be applied to \emph{sentential decision diagrams} (SDDs), a typically more compact but still canonical class of Boolean circuits, which generalizes OBDDs, while not being a subclass of BDDs. Here we fill this gap by deriving a general revision algorithm for SDDs based on a syntactic characterisation of Dalal revision. A specialised procedure for DNFs is also presented. Preliminary experiments performed with randomly generated knowledge bases show the advantages of directly perform revision within SDD formalism.

Keywords

Cite

@article{arxiv.2201.08112,
  title  = {Belief Revision in Sentential Decision Diagrams},
  author = {Lilith Mattei and Alessandro Facchini and Alessandro Antonucci},
  journal= {arXiv preprint arXiv:2201.08112},
  year   = {2022}
}

Comments

Extended version with proofs of a paper under review

R2 v1 2026-06-24T08:56:25.115Z