This paper proposes the methods to solve the constraint satisfaction problems (CSPs) using Q'tron neural networks (NNs). A Q'tron NN is local-minima free if it is built ...
Abstract. The input to a constraint satisfaction problem (CSP) consists of a set of variables, each with a domain, and constraints between these variables formulated by relations o...
The class Max (r, 2)-CSP consists of constraint satisfaction problems with at most two r-valued variables per clause. For instances with n variables and m binary clauses, we presen...
Attempts at classifying computational problems as polynomial time solvable, NP-complete, or belonging to a higher level in the polynomial hierarchy, face the difficulty of undecid...
Abstract. In constraint satisfaction, a general rule is to tackle the hardest part of a search problem first. In this paper, we introduce a parameter (τ) that measures the constr...