Efficient Sampling with Small Populations : a Genetic Algorithm Satisfying Detailed Balance. / Watkins, Christopher; Buttkewitz, Yvonne.

Gecco Companion '15: Proceedings of the Companion Publication of the 2015 Genetic and Evolutionary Computation Conference. 2015. p. 1517-1518.

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Abstract

We present a population genetic algorithm which satisfies detailed balance, and which has a stationary distribution that factorises into an explicit form for arbitrary fitness functions. For a population size of 1, it is the Metropolis algorithm with a ‘breeder’ proposal distribution; it extends to larger populations in a natural way, and the stationary (that is, the mutation-selection equilibrium) distribution is exactly known in a simple form for any population size. We term this algorithm exchangeable breeding tuple product sampling (EBT).
EBT is closely related to some non-parametric Bayesian Markov-chain Monte Carlo sampling algorithms. EBT can also be viewed as a generalisation of the Moran process.
Original languageEnglish
Title of host publicationGecco Companion '15
Subtitle of host publicationProceedings of the Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
Pages1517-1518
Number of pages2
ISBN (Electronic)978-1-4503-3488-4
DOIs
Publication statusPublished - 11 Jul 2015
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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