4,310 research outputs found
Existence versus Exploitation: The Opacity of Backbones and Backdoors Under a Weak Assumption
Backdoors and backbones of Boolean formulas are hidden structural properties.
A natural goal, already in part realized, is that solver algorithms seek to
obtain substantially better performance by exploiting these structures.
However, the present paper is not intended to improve the performance of SAT
solvers, but rather is a cautionary paper. In particular, the theme of this
paper is that there is a potential chasm between the existence of such
structures in the Boolean formula and being able to effectively exploit them.
This does not mean that these structures are not useful to solvers. It does
mean that one must be very careful not to assume that it is computationally
easy to go from the existence of a structure to being able to get one's hands
on it and/or being able to exploit the structure.
For example, in this paper we show that, under the assumption that P
NP, there are easily recognizable families of Boolean formulas with strong
backdoors that are easy to find, yet for which it is hard (in fact,
NP-complete) to determine whether the formulas are satisfiable. We also show
that, also under the assumption P NP, there are easily recognizable sets
of Boolean formulas for which it is hard (in fact, NP-complete) to determine
whether they have a large backbone
Quantum adiabatic optimization and combinatorial landscapes
In this paper we analyze the performance of the Quantum Adiabatic Evolution
algorithm on a variant of Satisfiability problem for an ensemble of random
graphs parametrized by the ratio of clauses to variables, . We
introduce a set of macroscopic parameters (landscapes) and put forward an
ansatz of universality for random bit flips. We then formulate the problem of
finding the smallest eigenvalue and the excitation gap as a statistical
mechanics problem. We use the so-called annealing approximation with a
refinement that a finite set of macroscopic variables (versus only energy) is
used, and are able to show the existence of a dynamic threshold
starting with some value of K -- the number of variables in
each clause. Beyond dynamic threshold, the algorithm should take exponentially
long time to find a solution. We compare the results for extended and
simplified sets of landscapes and provide numerical evidence in support of our
universality ansatz. We have been able to map the ensemble of random graphs
onto another ensemble with fluctuations significantly reduced. This enabled us
to obtain tight upper bounds on satisfiability transition and to recompute the
dynamical transition using the extended set of landscapes.Comment: 41 pages, 10 figures; added a paragraph on paper's organization to
the introduction, fixed reference
The Complexity of Reasoning with FODD and GFODD
Recent work introduced Generalized First Order Decision Diagrams (GFODD) as a
knowledge representation that is useful in mechanizing decision theoretic
planning in relational domains. GFODDs generalize function-free first order
logic and include numerical values and numerical generalizations of existential
and universal quantification. Previous work presented heuristic inference
algorithms for GFODDs and implemented these heuristics in systems for decision
theoretic planning. In this paper, we study the complexity of the computational
problems addressed by such implementations. In particular, we study the
evaluation problem, the satisfiability problem, and the equivalence problem for
GFODDs under the assumption that the size of the intended model is given with
the problem, a restriction that guarantees decidability. Our results provide a
complete characterization placing these problems within the polynomial
hierarchy. The same characterization applies to the corresponding restriction
of problems in first order logic, giving an interesting new avenue for
efficient inference when the number of objects is bounded. Our results show
that for formulas, and for corresponding GFODDs, evaluation and
satisfiability are complete, and equivalence is
complete. For formulas evaluation is complete, satisfiability
is one level higher and is complete, and equivalence is
complete.Comment: A short version of this paper appears in AAAI 2014. Version 2
includes a reorganization and some expanded proof
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