Discrete-time signal processing
Discrete-time signal processing
Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms
Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms
A tractable Walsh analysis of SAT and its implications for genetic algorithms
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Digital Signal Processing Algorithms: Number Theory, Convolutions, Fast Fourier Transforms, and Applications
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
Evolutionary Computation
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Further Experimentations on the Scalability of the GEMGA
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Genetic algorithms as function optimizers
Genetic algorithms as function optimizers
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Walsh transforms, balanced sum theorems and partition coefficients over multary alphabets
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Gene Expression and Fast Construction of Distributed Evolutionary Representation
Evolutionary Computation
Efficient Linkage Discovery by Limited Probing
Evolutionary Computation
General cardinality genetic algorithms
Evolutionary Computation
The simple genetic algorithm and the walsh transform: Part i, theory
Evolutionary Computation
The simple genetic algorithm and the walsh transform: Part ii, the inverse
Evolutionary Computation
Predicting epistasis from mathematical models
Evolutionary Computation
Scalability problems of simple genetic algorithms
Evolutionary Computation
Fda -a scalable evolutionary algorithm for the optimization of additively decomposed functions
Evolutionary Computation
Linkage identification by non-monotonicity detection for overlapping functions
Evolutionary Computation
IEEE Transactions on Evolutionary Computation
On the convergence of a class of estimation of distribution algorithms
IEEE Transactions on Evolutionary Computation
Extended probe method for linkage discovery over high-cardinality alphabets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
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Working under the premise that most optimizable functions are of bounded epistasis, this paper addresses the problem of discovering the linkage structure of a black-box function with a domain of arbitrary-cardinality under the assumption of bounded epistasis. To model functions of bounded epistasis, we develop a generalization of the mathematical model of "embedded landscapes" over domains of cardinality M. We then generalize the Walsh transform as a discrete Fourier transform, and develop algorithms for linkage learning of epistatically bounded GELs. We propose Generalized Embedding Theorem that models the relationship between the underlying decomposable structure of GEL and its Fourier coefficients. We give a deterministic algorithm to exactly calculate the Fourier coefficients of GEL with bounded epistasis. Complexity analysis shows that the epistatic structure of epistatically bounded GEL can be obtained after a polynomial number of function evaluations. Finally, an example experiment of the algorithm is presented.