1,140 research outputs found
On variables with few occurrences in conjunctive normal forms
We consider the question of the existence of variables with few occurrences
in boolean conjunctive normal forms (clause-sets). Let mvd(F) for a clause-set
F denote the minimal variable-degree, the minimum of the number of occurrences
of variables. Our main result is an upper bound mvd(F) <= nM(surp(F)) <=
surp(F) + 1 + log_2(surp(F)) for lean clause-sets F in dependency on the
surplus surp(F).
- Lean clause-sets, defined as having no non-trivial autarkies, generalise
minimally unsatisfiable clause-sets.
- For the surplus we have surp(F) <= delta(F) = c(F) - n(F), using the
deficiency delta(F) of clause-sets, the difference between the number of
clauses and the number of variables.
- nM(k) is the k-th "non-Mersenne" number, skipping in the sequence of
natural numbers all numbers of the form 2^n - 1.
We conjecture that this bound is nearly precise for minimally unsatisfiable
clause-sets.
As an application of the upper bound we obtain that (arbitrary!) clause-sets
F with mvd(F) > nM(surp(F)) must have a non-trivial autarky (so clauses can be
removed satisfiability-equivalently by an assignment satisfying some clauses
and not touching the other clauses). It is open whether such an autarky can be
found in polynomial time.
As a future application we discuss the classification of minimally
unsatisfiable clause-sets depending on the deficiency.Comment: 14 pages. Revision contains more explanations, and more information
regarding the sharpness of the boun
Truth Degrees Theory and Approximate Reasoning in 3-Valued Propositional Pre-Rough Logic
By means of the function induced by a logical formula A, the concept of truth degree of the logical formula A is introduced in the 3-valued pre-rough logic in this paper. Moreover, similarity degrees among formulas are proposed and a pseudometric is defined on the set of formulas, and hence a possible framework suitable for developing approximate reasoning theory in 3-value logic pre-rough logic is established
A Coverage Criterion for Spaced Seeds and its Applications to Support Vector Machine String Kernels and k-Mer Distances
Spaced seeds have been recently shown to not only detect more alignments, but
also to give a more accurate measure of phylogenetic distances (Boden et al.,
2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lower
misclassification rate when used with Support Vector Machines (SVMs) (On-odera
and Shibuya, 2013), We confirm by independent experiments these two results,
and propose in this article to use a coverage criterion (Benson and Mak, 2008,
Martin, 2013, Martin and No{\'e}, 2014), to measure the seed efficiency in both
cases in order to design better seed patterns. We show first how this coverage
criterion can be directly measured by a full automaton-based approach. We then
illustrate how this criterion performs when compared with two other criteria
frequently used, namely the single-hit and multiple-hit criteria, through
correlation coefficients with the correct classification/the true distance. At
the end, for alignment-free distances, we propose an extension by adopting the
coverage criterion, show how it performs, and indicate how it can be
efficiently computed.Comment: http://online.liebertpub.com/doi/abs/10.1089/cmb.2014.017
A Proof Theoretic View of Constraint Programming
We provide here a proof theoretic account of constraint programming that
attempts to capture the essential ingredients of this programming style. We
exemplify it by presenting proof rules for linear constraints over interval
domains, and illustrate their use by analyzing the constraint propagation
process for the {\tt SEND + MORE = MONEY} puzzle. We also show how this
approach allows one to build new constraint solvers.Comment: 25 page
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