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general.hpp File Reference

On investigations regarding the hardness of representations of boolean functions. More...

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Detailed Description

On investigations regarding the hardness of representations of boolean functions.

Todo:
Connections
Todo:
Hardness of boolean function representations
  • The hardness h(F) of a CNF F is defined to be the minimum k such that for all implicates C of F, we have that r_k(phi_C * F) yields the empty clause.
  • We have that:
    • h(F) = 0 if F contains all its prime implicates.
    • h(F) <= h(F') where F' is the canonical (full) CNF representation of F.
    • If F is a full clause-set, i.e., only clauses of length n(F)), then h(F) = n(F) - m where m is the size of a prime implicate of F with the minimum clause-length.
    • If F is renamable horn, then h(F) <= 1.
    • If F is a 2-CNF clause-set, then h(F) <= 2.
  • For a boolean function f the "hardest" representation F, without new variables, is the canonical CNF representation of f. This follows from the fact that for every partial assignment phi, applying phi to F yields the canonical unsatisfiable CNF on the remaining variables, which is of maximum hardness.
  • How does this hardness notion relate to the performance of SAT solvers on existing problems?
  • Investigations into how representations with different hardness affect SAT solving is being investigated in:
  • The hardness of the following should be investigated:
  • Computing the hardness of small functions:
    • We do not, in general, compute the hardness of boolean function representations, but construct representations with low hardness.
    • However, for experimental evaluation and curiousities sake, we can and should measure the hardness of certain representations of small boolean functions.
    • For example, we should measure the hardness of the minimum representations of the DES and AES boxes. See AdvancedEncryptionStandard/plans/Representations/general.hpp.
    • We have the Maxima-functions hardness_wpi_cs, hardness_cs, and hardness_u_cs for computing hardness.
Todo:
Propagation hardness of 2-CNF
  • F in 2-CLS should even have phardness(F) <= 2.
  • This should be investigated also experimentally (to strengthen our system).
Todo:
Hardness of canonical translation of positive DNF
  • For a positive DNF-clause-set F, the set of CNF-prime-clauses is the transversal hypergraph of F, with element-wise negation.
  • One would guess that if F is far away from a variable-disjoint hitting clause-set, then the canonical translation dualts_cs(F) should have high hardness.
  • The boolean function of the DNF F could then also have the property of not having a small CNF-representation of small hardness.
  • If F is a positive 2-CLS, then we have hardness at most 1:
    test1(n) := hardness_cs(dualts_cs(powerset(setn(n),2)))$
       
    n <= 1 yield hardness 0, all other n yield hardness 1.
  • 3-CLS:
    hardness_cs(dualts_cs({{1,2,3},{2,3,4}});
      1
       
Todo:
Hardness of Sudoku problems
  • As discussed in "Finding hard instances for box-dimension 3" in Investigations/LatinSquares/Sudoku/plans/general.hpp, the right approach for determining the "hardness" of Sudoku problems should be to determine their t-, p- and w-hardness!
  • Also the direct encoding is very natural here.
  • An article about this should be very attractive!
  • For this we need hardness-computation at C++ level.

Definition in file general.hpp.