Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings)
Elliot Meyerson,
Xin Qiu,
Risto Miikkulainen
Abstract:This paper characterizes the inherent power of evolutionary algorithms. This power depends on the computational properties of the genetic encoding. With some encodings, two parents recombined with a simple crossover operator can sample from an arbitrary distribution of child phenotypes. Such encodings are termed expressive encodings in this paper. Universal function approximators, including popular evolutionary substrates of genetic programming and neural networks, can be used to construct expressive encodings… Show more
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