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Found 17 papers, 2 papers with code
Finding Near-Optimal Portfolios With Quality-Diversity
In this paper, we present a novel approach for finding a diverse set of such portfolios based on quality-diversity (QD) optimization.
A Systematic Evaluation of Evolving Highly Nonlinear Boolean Functions in Odd Sizes
In the last 30 years, evolutionary algorithms have been shown to be a strong option for evolving Boolean functions in different sizes and with different properties.
Look into the Mirror: Evolving Self-Dual Bent Boolean Functions
This paper provides a detailed experimentation with evolutionary algorithms with the goal of evolving (anti-)self-dual bent Boolean functions.
A New Angle: On Evolving Rotation Symmetric Boolean Functions
Rotation symmetric Boolean functions represent an interesting class of Boolean functions as they are relatively rare compared to general Boolean functions.
Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions
By observing the range of possible changes an operator can provide, as well as relative probabilities of specific transitions in the objective space, one can use this information to design a more effective combination of genetic operators.
On the Evolution of Boomerang Uniformity in Cryptographic S-boxes
One example of such a property is called boomerang uniformity, which helps to be resilient against boomerang attacks.
Evolving Constructions for Balanced, Highly Nonlinear Boolean Functions
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.
Evolutionary Construction of Perfectly Balanced Boolean Functions
Finding Boolean functions suitable for cryptographic primitives is a complex combinatorial optimization problem, since they must satisfy several properties to resist cryptanalytic attacks, and the space is very large, which grows super exponentially with the number of input variables.
Modeling Strong Physically Unclonable Functions with Metaheuristics
While there is no reason to doubt the performance of CMA-ES, the lack of comparison with different metaheuristics and results for the challenge-response pair-based attack leaves open questions if there are better-suited metaheuristics for the problem.
On the Difficulty of Evolving Permutation Codes
Combinatorial designs provide an interesting source of optimization problems.
Building the Building Blocks: From Simplification to Winning Trees in Genetic Programming
The winning trees can be used to initialize the population for the new GP run and result in improved convergence and fitness, provided some conditions on the size of solutions and winning trees are fulfilled.
Evolutionary Algorithms for Designing Reversible Cellular Automata
Reversible Cellular Automata (RCA) are a particular kind of shift-invariant transformations characterized by a dynamics composed only of disjoint cycles.
On the Genotype Compression and Expansion for Evolutionary Algorithms in the Continuous Domain
This paper investigates the influence of genotype size on evolutionary algorithms' performance.
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations
Genetic programming is an often-used technique for symbolic regression: finding symbolic expressions that match data from an unknown function.
CoInGP: Convolutional Inpainting with Genetic Programming
In the second experiment, we train a GP convolutional predictor on two degraded images, removing around 20% of their pixels.
Towards an evolutionary-based approach for natural language processing
Tasks related to Natural Language Processing (NLP) have recently been the focus of a large research endeavor by the machine learning community.
A characterisation of S-box fitness landscapes in cryptography
Substitution Boxes (S-boxes) are nonlinear objects often used in the design of cryptographic algorithms.
