scholarly journals Algebraic Simplification Techniques for Propositional Satisfiability

Author(s):  
João Marques-Silva
10.29007/7n71 ◽  
2018 ◽  
Author(s):  
Steffen Hölldobler ◽  
Norbert Manthey ◽  
Tobias Philipp ◽  
Peter Steinke

Modern propositional satisfiability (or SAT) solvers are very powerful due to recent developments on the underlying data structures, the used heuristics to guide the search, the deduction techniques to infer knowledge, and the formula simplification techniques that are used during pre- and inprocessing. However, when all these techniques are put together, the soundness of the combined algorithm is not guaranteed any more, and understanding the complex dependencies becomes non-trivial.In this paper we present a small set of rules that allows to model modern SAT solvers in terms of a state transition system. With these rules all techniques which are applied in modern SAT solvers can be modeled adequately. Furthermore, we show that this set of rules results is sound, complete and confluent. Finnaly, we compare the proposed transition system to related systems, and show how widely used solving techniques can be modeled.


2014 ◽  
Vol 35 (3) ◽  
pp. 742-748
Author(s):  
Hong-bo Gao ◽  
Qing-bao Li ◽  
Wei Wang ◽  
Yu Zhu

1959 ◽  
Vol 24 (1) ◽  
pp. 17-19 ◽  
Author(s):  
B. Dunham ◽  
R. Fridshal

By quite elementary means, one can find “large” examples difficult, if not (for practical purposes) impossible, to be managed by that host of methods, after Quine, for minimizing expressions in alternational normal form. Because the workability rather than existence of an algorithm for minimizing logical formulae is generally critical, it may be pertinent to outline briefly the derivation of these “large” examples. Some more general insight may also be gained about simplification techniques.


Author(s):  
R. W. Toogood

Abstract A number of programs have been developed for the automatic symbolic generation of efficient computer code for the dynamic analysis of serial rigid and flexible link manipulators. Code for both the inverse and the direct dynamics computations can be generated. The symbolic generators allow the robot base to be given an arbitrary linear acceleration anchor angular velocity and acceleration. The efficiency of the generated code is an important consideration for simulation studies and/or implementation in control systems. This paper briefly describes the symbolic generation and simplification techniques. The added computational load due to including the base motion is discussed. Some dynamics simulation results are presented for a 3R rigid link manipulator mounted on an oscillating base, which graphically illustrates the effect of the base movement on the dynamics.


Author(s):  
Frank Neumann ◽  
Andrew M. Sutton

We study the ability of a simple mutation-only evolutionary algorithm to solve propositional satisfiability formulas with inherent community structure. We show that the community structure translates to good fitness-distance correlation properties, which implies that the objective function provides a strong signal in the search space for evolutionary algorithms to locate a satisfying assignment efficiently. We prove that when the formula clusters into communities of size s ∈ ω(logn) ∩O(nε/(2ε+2)) for some constant 0


Author(s):  
Giovanni Amendola ◽  
Carmine Dodaro ◽  
Marco Maratea

The issue of describing in a formal way solving algorithms in various fields such as Propositional Satisfiability (SAT), Quantified SAT, Satisfiability Modulo Theories, Answer Set Programming (ASP), and Constraint ASP, has been relatively recently solved employing abstract solvers. In this paper we deal with cautious reasoning tasks in ASP, and design, implement and test novel abstract solutions, borrowed from backbone computation in SAT. By employing abstract solvers, we also formally show that the algorithms for solving cautious reasoning tasks in ASP are strongly related to those for computing backbones of Boolean formulas. Some of the new solutions have been implemented in the ASP solver WASP, and tested.


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