CodingTrain / CodingTrain/Suggestion-Box
Evolution time
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Descripción
I have an idea of decreasing evolution time by shifting gene index for fitness calculation.
Suppose we want to generate "To be or not to be". We compare every single letter to the result every time we want to calculate fitness. Code below increases comparing gene index starting point by 1 every 10th generation is made. Every time fitness calculation is active, comparing gene index will increase by 3.
The question arises. How can we be sure that every 3rd gene with starting point of 1 and 2 is "correct" after 20 generations? Maybe new way of reproduction or just adding an inspection array in fitness calculation method?
public class Evolution {
private final int TIME_INTERVAL = 10;
private final int GENE_SHIFT = 3;
private int geneStart = 0;
public Evolution(DNA resultDNA) {
startEvolution(resultDNA);
}
public void startEvolution(DNA resultDNA) {
initializePopulation();
int counter = 0;
while(true) {
counter++;
if(counter > TIME_INTERVAL) {
geneStart++;
if(geneStart > GENE_SHIFT - 1) {
geneStart = 0;
}
counter = 0;
}
calculateFitness(resultDNA.getGenes());
doSelection();
doReproduction();
if(evaluationOK()) {
break;
}
}
}
private void calculateFitness(Gene[] resultGenes) {
for(DNA dna : population) {
Gene[] genes = dna.getGenes();
dna.setFitness(0);
int i = geneStart;
while(i < genes.length) {
if(genes[i] == resultGenes[i]) {
dna.increaseFitness();
}
i += GENE_SHIFT;
}
}
}
private void doSelection() {
//...
}
private void doReproduction() {
//...
}
}
Guía de contribución
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Línea de trabajo
No repository file, test, or entry point is named. Start by locating any existing evolution or fitness-calculation implementation related to this proposal, then review whether the gene-shifting approach preserves fitness coverage across generations. Done is not defined by the issue; a contributor would need an agreed algorithm and validation criteria first.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- java
- Área
- machine-learning
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Estancado
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 20/100