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In your version of flappy bird, the score is assigned based on the distance traveled. Hence, there's no way a bird has score = 0 in a generation. But, in my version, I have assigned points based on the number of pipes crossed. And there's a good chance none of the birds make it in the first generation. Hence, the total score of the generation = 0;
In your version of flappy bird, the score is assigned based on the distance traveled. Hence, there's no way a bird has score = 0 in a generation. But, in my version, I have assigned points based on the number of pipes crossed. And there's a good chance none of the birds make it in the first generation. Hence, the total score of the generation = 0;
https://github.com/shiffman/NOC-S18/blob/95b801d6e0cefeb9b8d2ac1997d0b68bb46d95d7/week10/neuroevolution-flappybird/ga.js#L75-L79
In this algorithm, since r remains constant the loop runs forever until the index > birds.
https://github.com/shiffman/NOC-S18/blob/95b801d6e0cefeb9b8d2ac1997d0b68bb46d95d7/week10/neuroevolution-flappybird/ga.js#L56-L59
Likewise while calculating the fitness, the scores will be divided by zero resulting in NaN fitness for all birds
How can these issues be solved without changing the scoring system ?
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