GSAT with adaptive score function

GSAT with Adaptive Score Function

Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract GSAT is a well-known satisfiability search algorithm. In this paper we consider a modification of GSAT. In particular, we consider an adaptive score function. Investigation of efficient satisfiability algorithms and encoding d...

Algorithm 1 : The GSAT algorithm

GSAT is a greedy local search procedure. It searches for satissable instantiations of formulas under conjunctive normal form. Intrinsically incomplete, this algorithm has shown its ability to deal with formulas of large size that are not yet accessible to exhaustive methods. Many problems such as planning, scheduling, vision can eeciently be solved by using the GSAT algorithm. In this study, we...

Criticality and Parallelism in GSAT

Blind Source Separation by Adaptive Estimation of Score Function Difference

In this paper, an adaptive algorithm for blind source separation in linear instantaneous mixtures is proposed, and it is shown to be the optimum version of the EASI algorithm. The algorithm is based on minimization of mutual information of outputs. This minimization is done using adaptive estimation of a recently proposed non-parametric “gradient” for mutual information.

GSAT and Local Consistency

It has been shown that hill-climbing constraint satisfaction methods like min-con icts [ Minton et al., 1990 ] and GSAT [ Selman et al., 1992 ] can outperform complete systematic search methods like backtracking and backjumping on many large classes of problems. In this paper we investigate how preprocessing improves GSAT. In particular, we will focus on the effect of enforcing local consistenc...