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Paradigms for using neural networks (NNs) and genetic algorithms (GAs) to heuristicaJIy solve boolean satisfiability (SAT) problems are presented. Since SAT is NP-Complete, any olher NP-Compleie problem can be transformed into an equivalent SAT problem in polynomial Lime, and solved via either paradigm. This technique is illustrated for hamiltonian circuit (HC) problems.

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