Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence SDD: A New Canonical Representation of Propositional Knowledge Bases

Citations in the corpus

• DeepProbLog: Neural Probabilistic Logic Programming (2018, methodology): “(iii) The third step compiles the logic formula into a Sentential Decision Diagram (SDD, Darwiche [2011]), a form that allows for efficient evaluation of the query, using knowledge compilation technology [Darwiche and Marquis, 2002].”
• Three Modern Roles for Logic in AI (2020, methodology): “DDs, then conjoining or disjoining the SDDs takes O(s ·t)time, although the resulting SDD may not be compressed [89]. Compression is a property that ensures the canonicity of an SDD for a given vtree [28]. Figure 11: OBDD fragment and corresponding NNF circuit. cases [12, 93]. Recall that E-MajSat a”
• A Semantic Loss Function for Deep Learning with Symbolic Knowledge (2017, methodology): “We use the language and circuit compilation techinques described in Darwiche (2011) to build a Boolean circuit representing (Darwiche & Marquis, 2002).”