An introduction to genetic algorithms
An introduction to genetic algorithms
Landscapes and molecular evolution
Proceedings of the 16th annual international conference of the Center for Nonlinear Studies on Landscape paradigms in physics and biology : concepts, structures and dynamics: concepts, structures and dynamics
Ruggedness and neutrality—the NKp family of fitness landscapes
ALIFE Proceedings of the sixth international conference on Artificial life
How neutral networks influence evolvability
Complexity
Through the Labyrinth Evolution Finds a Way: A Silicon Ridge
ICES '96 Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware
The Advantages of Landscape Neutrality in Digital Circuit Evolution
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Neutrality and the Evolvability of Boolean Function Landscape
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
An empirical investigation of how and why neutrality affects evolutionary search
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Representations for Genetic and Evolutionary Algorithms
Representations for Genetic and Evolutionary Algorithms
On the roles of redundancy and neutrality in evolutionary optimization: an experimental study
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A study of NK landscapes' basins and local optima networks
Proceedings of the 10th annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
FOGA'07 Proceedings of the 9th international conference on Foundations of genetic algorithms
Redundancy and computational efficiency in Cartesian genetic programming
IEEE Transactions on Evolutionary Computation
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Some authors consider that evolutionary search may be positively influenced by the use of redundant representations, whereas others note that the addition of random redundancy to a representation could be useless in optimization. Given this lack of consensus, two new families of redundant binary representations are developed in this paper. The first family is based on linear transformations and is considered non-neutral. The second family of representations is designed to implement neutrality, and is based on the mathematical formulation of error control codes. A study aimed at assessing the influence of redundancy and neutrality on the performance of a simple evolutionary hillclimber is presented. The 1+1-ES is modeled using Markov chains and is applied to NK fitness landscapes. The results indicate that the phenotypic neighborhood induced by a redundant representation dominates the behavior of the algorithm, affecting the search more strongly than neutrality, and the representations with better performance on NK fitness landscapes do not exhibit extreme values of any of the indicators of representation quality commonly adopted in the literature.