Asymptotical convergence rates of simple evolutionary algorithms under factorizing mutation distributions

Modularity is a system property of many natural and artificial adaptive systems. Evolutionary algorithms designed to produce modular solutions have increased convergence rates and improved generalization ability; however, their performance can be impacted if the task is inherently nonmodular. Previously, we have shown that some design variables can influence whether the task on the remaining variables is inherently modular. We investigate the possibility of exploiting that dependence to simplify optimization and arrive at a general design pattern that we use to show that evolutionary search can seek such modularity-inducing design variable values, thus easing subsequent search for highly fit, modular organization within the remaining design variables. We investigate this approach with embodied agents in which evolutionary discovery of morphology enables subsequent discovery of highly fit, modular controllers and show that it benefits from biasing search toward modular controllers and setting the mutation rate for control policies higher than that for morphology. This work also reinforces our previous finding that the relationship between modularity and evolvability that is well-studied in nonembodied systems can, under certain conditions, be generalized to include embodied systems as well and provides a practical approach to satisfying the conditions in question.

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Local convergence rates of simple evolutionary algorithms with Cauchy mutations

IEEE Transactions on Evolutionary Computation ◽

10.1109/4235.687885 ◽

1997 ◽

Vol 1 (4) ◽

pp. 249-258 ◽

Cited By ~ 80

Author(s):

G. Rudolph

Keyword(s):

Evolutionary Algorithms ◽

Local Convergence ◽

Convergence Rates

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THE CONVERGENCE RATES OF EMPIRICAL BAYES ESTIMATION FOR PARAMETERS OF TWO-SIDED TRUNCATION DISTRIBUTION FAMILIES

Acta Mathematica Scientia ◽

10.1016/s0252-9602(18)30366-7 ◽

1989 ◽

Vol 9 (4) ◽

pp. 403-413

Author(s):

Laisheng Wei

Keyword(s):

Empirical Bayes ◽

Convergence Rates ◽

Bayes Estimation ◽

Empirical Bayes Estimation

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THE CONVERGENCE RATES OF ASYMPTOTICALLY BAYES DISCRIMINATION

Acta Mathematica Scientia ◽

10.1016/s0252-9602(18)30690-8 ◽

1985 ◽

Vol 5 (1) ◽

pp. 67-78

Author(s):

Laisheng Wei

Keyword(s):

Convergence Rates

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Opponent Center-Surround Contrast: Colour to Grey Conversion

London Imaging Meeting ◽

10.2352/issn.2694-118x.2020.lim-18 ◽

2020 ◽

Vol 2020 (1) ◽

pp. 105-108

Author(s):

Ali Alsam

Keyword(s):

Evolutionary Algorithms ◽

Three Dimensional ◽

The State ◽

Colour Space ◽

Vision Science ◽

State Of Art ◽

Over Time

Vision is the science that informs us about the biological and evolutionary algorithms that our eyes, opticnerves and brains have chosen over time to see. This article is an attempt to solve the problem of colour to grey conversion, by borrowing ideas from vision science. We introduce an algorithm that measures contrast along the opponent colour directions and use the results to combine a three dimensional colour space into a grey. The results indicate that the proposed algorithm competes with the state of art algorithms.

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