Evolving constructions for balanced, highly nonlinear boolean functions
Claude Carlet, Marko Djurasevic, Domagoj Jakobović, Luca Mariot, Stjepan Picek
2022Proceedings of the Genetic and Evolutionary Computation Conference11 citationsDOIOpen Access PDF
Abstract
Finding balanced, highly nonlinear Boolean functions is a difficult problem where it is not known what nonlinearity values are possible to be reached in general. At the same time, evolutionary computation is successfully used to evolve specific Boolean function instances, but the approach cannot easily scale for larger Boolean function sizes. Indeed, while evolving smaller Boolean functions is almost trivial, larger sizes become increasingly difficult, and evolutionary algorithms perform suboptimally.
Topics & Concepts
Boolean functionMaximum satisfiability problemBoolean circuitStandard Boolean modelBoolean expressionBoolean networkParity functionAnd-inverter graphProduct termComputer scienceComputationTheoretical computer scienceFunction (biology)Two-element Boolean algebraCircuit minimization for Boolean functionsNonlinear systemMathematicsAlgorithmAlgebra over a fieldPure mathematicsQuantum mechanicsBiologyFiltered algebraPhysicsEvolutionary biologyEvolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms ResearchReceptor Mechanisms and Signaling