博文
Learning NetLogo: Note 01
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Requirements: 1)the number of individuals in a population is set to be fixed at N across generations; 2) the number of carriers of the i-th genotype is set to be a variable Ni; 3)Ni may change over generations depending on the fitness of the the i-th genotype while N remains fixed.
Ways of fulfillment in NetLogo:
An example is seen in Novak & Wilensky's 'Bug Hunt Coevolution' model, where the way of embodying the fitness is to ask each individual to die if it fulfills a certain criterion (here it's lack of energy to a certain extent), and to randomly ask one of the rest individuals to reproduce +1 once an individual dies.
Why not ask the individual with highest energy to reproduce? As I understand the selection force will become stronger in the model if so. Now the point is what's the real-world case. Actually we have a few alternative ways of manifesting the fitness in the model.
1) The way introduced by the authors (weak selection; the worst may be eliminated finally but the best may not win);
2) As said above, ask the individual with the lowest energy to die and the one with the highest to multiply (strong directed selection);
3) Ask the individual with the highest energy to multiply, meanwhile ask a randomly selected individual from the rest of the population to die (weak selection; the best may win finally but the worst may never be eliminated);
4) Create a table with fitness (or energy) of each genotype, and ask a planned number of individuals of each genotype to die or multiply based on a comprehensive calculation.
I would say, the fourth way is actually not an agent-based model any more. However, our decision of which way to be used depends on characteristics of the studied organisms/people in real world.
https://blog.sciencenet.cn/blog-351781-637588.html
上一篇：Disputation on evol-cancer research 02
下一篇：关于人工神经网络的一点心得
Ways of fulfillment in NetLogo:
An example is seen in Novak & Wilensky's 'Bug Hunt Coevolution' model, where the way of embodying the fitness is to ask each individual to die if it fulfills a certain criterion (here it's lack of energy to a certain extent), and to randomly ask one of the rest individuals to reproduce +1 once an individual dies.
Why not ask the individual with highest energy to reproduce? As I understand the selection force will become stronger in the model if so. Now the point is what's the real-world case. Actually we have a few alternative ways of manifesting the fitness in the model.
1) The way introduced by the authors (weak selection; the worst may be eliminated finally but the best may not win);
2) As said above, ask the individual with the lowest energy to die and the one with the highest to multiply (strong directed selection);
3) Ask the individual with the highest energy to multiply, meanwhile ask a randomly selected individual from the rest of the population to die (weak selection; the best may win finally but the worst may never be eliminated);
4) Create a table with fitness (or energy) of each genotype, and ask a planned number of individuals of each genotype to die or multiply based on a comprehensive calculation.
I would say, the fourth way is actually not an agent-based model any more. However, our decision of which way to be used depends on characteristics of the studied organisms/people in real world.
https://blog.sciencenet.cn/blog-351781-637588.html
上一篇：Disputation on evol-cancer research 02
下一篇：关于人工神经网络的一点心得
