• Source: 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 diagram classes include OBDDs, FBDDs, and non-deterministic OBDDs, as well as MDD.
      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], and CCDD


      References

    Kata Kunci Pencarian: