Knowledge compilation
Knowledge compilation is a family of approaches for addressing the intractability of
a number of artificial intelligence problems.
A propositional model is compiled in an off-line phase in order to support some queries in polynomial time. Many ways of compiling a propositional model exist.
Different compiled representations have different properties.
The three main properties are:
- The compactness of the representation
- The queries that are supported in polynomial time
- The transformations of the representations that can be performed in polynomial time
Classes of representations
Some examples of formula classes include DNF and CNF.
Examples of circuit classes include NNF, DNNF, d-DNNF, and SDD.
Knowledge compilers
- c2d: supports compilation to d-DNNF
- d4: supports compilation to d-DNNF
- miniC2D: supports compilation to SDD
- KCBox: supports compilation to OBDD, OBDD, and CCDD