An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Compositional Evolution: The Impact of Sex, Symbiosis, and Modularity on the Gradualist Framework of Evolution (Vienna Series in Theoretical Biology)
Proceedings of the 9th annual conference on Genetic and evolutionary computation
How different hierarchical relationships impact evolution
ACAL'07 Proceedings of the 3rd Australian conference on Progress in artificial life
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We review recent work on the Hierarchical-If-And-Only-If problem and present a new hierarchical problem, HIFF-M that does not fit with previous explanations for evolutionary difficulty on hierarchical problems decomposed by levels for RMHC2. RMHC2 is a hill climbing algorithm augmented with a multi-level selection scheme. When used with the "ideal" sieve for a problem, as is done in this paper, RMHC2 exerts top-down control on the evolutionary dynamics, in the sense that adaptation of higher levels are given priority over adaptation of lower levels, and creates stabilizing selection pressure with potential to increase evolvability. Through HIFF-M, we discovered that the summary statistic, Fitness Distance Correlation by level, is not a reliable indicator of when a hierarchical problem is solvable by RMHC2, and that the two properties proposed to explain search easiness for RMHC2 are inadequate. Our investigation of this anomaly led us to propose an additional property for hierarchical evolution difficulty under RMHC2: inter-level conflict. We also discuss how hierarchical control can be subverted through the information transfer capacity of the transposition operation.