I have implemented a simple Genetic Algorithm to generate short story based on Aesop fables.
Here are the parameters I'm using:
Mutation: Single word swap mutation with tested rate with 0.01.
Crossover: Swap the story sentences at given point. rate – 0.7
Selection: Roulette wheel selection – https://stackoverflow.com/a/5315710/536474
Fitness function: 3 different function. highest score of each is 1.0. so total highest fitness score is 3.0.
Population size: Since I'm using 86 Aesop fables, I tested population size with 50.
Initial population: All 86 fable sentence orders are shuffled in order to make complete nonsense. And my goal is to generate something meaningful(at least at certain level) from these structure lost fables.
Stop Condition: 3000 generations.
And the results are below:
However, this still did not produce a favorable result. I was expecting the plot that goes up over the generations. Any ideas to why my GA performing worse result?
Update: As all of you suggested, I've employed elitism by 10% of current generation copied to next generation. Result still remains the same:
Probably I should use tournament selection.