Evolution of a Metaheuristic for Aggregating Wisdom from Artificial Crowds

Lowrance, Christopher J.; Abdelwahab, Omar; Yampolskiy, Roman V.

doi:10.1007/978-3-319-23485-4_24

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Evolutionary Computation1

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2018

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Cited by 3 publications

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“…From the early 1950s multiple well documents attempts to make Darwin's algorithm work on a computer have been published under such names as Evolutionary Programming [13], Evolutionary Strategies [14], Genetic Algorithms [15], Genetic Programming [16], Genetic Improvement [17], Gene Expression Programming [18], Differential Evolution [19], Neuroevolution [20] and Artificial Embryogeny [21]. While numerous variants different in their problem representation and metaheuristics exist [22][23][24][25], all can be reduced to just two main approaches -Genetic Algorithm (GA) and Genetic Programming (GA).…”

Section: Evolutionary Computationmentioning

confidence: 99%

Why We Do Not Evolve Software? Analysis of Evolutionary Algorithms

Yampolskiy

2018

Evol Bioinform Online

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In this article, we review the state-of-the-art results in evolutionary computation and observe that we do not evolve nontrivial software from scratch and with no human intervention. A number of possible explanations are considered, but we conclude that computational complexity of the problem prevents it from being solved as currently attempted. A detailed analysis of necessary and available computational resources is provided to support our findings.

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