## Abstract

An ongoing discussion in biology concerns whether intrinsic

mortality, or senescence, is programmed or not. The death

(i.e. removal) of an individual solution is an inherent feature

in evolutionary algorithms that can potentially explain how

intrinsic mortality can be beneficial in natural systems. This

paper investigates the relationship between mutation rate and

mortality rate with a steady state genetic algorithm that has a

specific intrinsic mortality rate. Experiments were performed

on a predefined deceptive fitness landscape, the hierarchical

if-and-only-if function (H-IFF). To test whether the relationship

between mutation and mortality rate holds for more complex

systems, an agent-based spatial grid model based on the

H-IFF function was also investigated. This paper shows that

there is a direct correlation between the evolvability of a population

and an indiscriminate intrinsic mortality rate to mutation

rate ratio. Increased intrinsic mortality or increased mutation

rate can cause a random drift that can allow a population

to find a global optimum. Thus, mortality in evolutionary

algorithms does not only explain evolvability, but might also

improve existing algorithms for deceptive/rugged landscapes.

Since an intrinsic mortality rate increases the evolvability of

our spatial model, we bolster the claim that intrinsic mortality

can be beneficial for the evolvability of a population.

mortality, or senescence, is programmed or not. The death

(i.e. removal) of an individual solution is an inherent feature

in evolutionary algorithms that can potentially explain how

intrinsic mortality can be beneficial in natural systems. This

paper investigates the relationship between mutation rate and

mortality rate with a steady state genetic algorithm that has a

specific intrinsic mortality rate. Experiments were performed

on a predefined deceptive fitness landscape, the hierarchical

if-and-only-if function (H-IFF). To test whether the relationship

between mutation and mortality rate holds for more complex

systems, an agent-based spatial grid model based on the

H-IFF function was also investigated. This paper shows that

there is a direct correlation between the evolvability of a population

and an indiscriminate intrinsic mortality rate to mutation

rate ratio. Increased intrinsic mortality or increased mutation

rate can cause a random drift that can allow a population

to find a global optimum. Thus, mortality in evolutionary

algorithms does not only explain evolvability, but might also

improve existing algorithms for deceptive/rugged landscapes.

Since an intrinsic mortality rate increases the evolvability of

our spatial model, we bolster the claim that intrinsic mortality

can be beneficial for the evolvability of a population.

Originalsprog | Engelsk |
---|---|

Titel | Artificial Life Conference Proceedings : ALIFE 2018 |

Antal sider | 8 |

Forlag | MIT Press |

Publikationsdato | 2018 |

Sider | 242-249 |

DOI | |

Status | Udgivet - 2018 |