Evolutionary programming - Wikiwand
Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover.[1][2] Evolutionary programming differs from evolution strategy ES(
It was first used by Lawrence J. Fogel in the US in 1960 in order to use simulated evolution as a learning process aiming to generate artificial intelligence.[4] It was used to evolve finite-state machines as predictors.[5]
More information Year, Description ...
Timeline of EP - selected algorithms[1]
| Year | Description | Reference |
|---|---|---|
| 1966 | EP introduced by Fogel et al. | [6] |
| 1992 | Improved fast EP - Cauchy mutation is used instead of Gaussian mutation | [7] |
| 2002 | Generalized EP - usage of Lévy-type mutation | [8] |
| 2012 | Diversity-guided EP - Mutation step size is guided by diversity | [9] |
| 2013 | Adaptive EP - The number of successful mutations determines the strategy parameter | [10] |
| 2014 | Social EP - Social cognitive model is applied meaning replacing individuals with cognitive agents | [11] |
| 2015 | Immunised EP - Artificial immune system inspired mutation and selection | [12] |
| 2016 | Mixed mutation strategy EP - Gaussian, Cauchy and Lévy mutations are used | [13] |
| 2017 | Fast Convergence EP - An algorithm, which boosts convergence speed and solution quality | [14] |
| 2017 | Immune log-normal EP - log-normal mutation combined with artificial immune system | [15] |
| 2018 | ADM-EP - automatically designed mutation operators | [16] |
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