Towards a knowledge compilation map for heterogeneous representation languages
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Constraint Satisfaction Problems (CSPs) offer a powerful framework for representing a great variety of problems. The difficulty is that most of the requests associated with CSPs are NP-hard. As these requests must be addressed online, Multivalued Decision Diagrams (MDDs) have been proposed as a way to compile CSPs. In the present paper, we draw a compilation map of MDDs, in the spirit of the NNF compilation map, analyzing MDDs according to their succinctness and to their playtime transformations and queries. Deterministic ordered MDDs are a generalization of ordered binary decision diagrams to non-Boolean domains: unsurprisingly, they have similar capabilities. More interestingly, our study puts forward the interest of non-deterministic ordered MDDs: when restricted to Boolean domains, this fragment captures OBDD and DNF as proper subsets and has performances close to those of DNNF. The comparison to classical, deterministic MDDs shows that relaxing the determinism requirement leads to an increase in succinctness and allows more transformations to be satisfied in polytime (typically, the disjunctive ones). Experiments on random problems confirm the gain in succinctness.