Population structure increases the evolvability of genetic algorithms

Hol, Felix J H; Wang, Xin; Keymer, Juan E.

doi:10.1002/cplx.21392

Cited by 1 publication

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“…Ever since Vito Volterra developed his famous predator–prey equations , continuous simulation has been used to represent artificial ecological systems . Discrete simulation has also been used frequently, using tools such as cellular automata and Lindenmayer systems . Agent‐based artificial life ecosystems are relatively old and have fused with artificial life research since the end of the 1980s (see for a relatively recent survey of the field).…”

Section: Introductionmentioning

confidence: 99%

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Evolving a predator–prey ecosystem of mathematical expressions with grammatical evolution

Alfonseca

Gil

2014

Complexity

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El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription This paper describes the use of grammatical evolution to obtain a predator-prey ecosystem of artificial beings associated with mathematical functions, whose fitness is also defined mathematically. The system supports the simultaneous evolution of several ecological niches and, through the use of standard measurements, makes it possible to explore the influence of the number of niches and the values of several parameters on "biological" diversity and similar functions. Sensitivity analysis tests have been made to find the effect of assigning different constant values to the genetic parameters that rule the evolution of the system and the predator-prey interaction, or of replacing them by functions of time. One of the parameters (predator efficiency) was found to have a critical range, outside which the ecologies are unstable; two others (genetic shortening rate and predator-prey fitness comparison logistic amplitude) are critical just at one side of the range), the others are not critical. The system seems quite robust, even when one or more parameters are made variable during a single experiment, without leaving their critical ranges. Our results also suggest that some of the features of biological evolution depend more on the genetic substrate and natural selection than on the actual phenotypic expression of that substrate.

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Section: Introductionmentioning

confidence: 99%

“…The environment is also very simple. In some ecological simulations, spatial distribution is important . Our agents, however, do not have a space location.…”

Section: Introductionmentioning

confidence: 99%

Evolving a predator–prey ecosystem of mathematical expressions with grammatical evolution

Alfonseca

Gil

2014

Complexity

View full text Add to dashboard Cite

show abstract

Population structure increases the evolvability of genetic algorithms

Cited by 1 publication

References 21 publications

Evolving a predator–prey ecosystem of mathematical expressions with grammatical evolution

Evolving a predator–prey ecosystem of mathematical expressions with grammatical evolution

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