Instead of cartesian coordinates, use polar coordinates. Given that Ash moves within a radius of 1000 during a turn, it will be easier to generate move commands
Hi,
oh, I see. and in the polar coordinates, the center O should be Ash, right? That would be easier for him to move.
Thanks!
Hi,
Iâve tried many combinations of {population size, crossover rate, mutation rate, elitism count}, but I cannot manage to have it converge on Test 09 Rectangle.
maxGenerations: 1000
PopulationSize: 100,
MutationRate: 0.05,
CrossoverRate: 0.95,
ElitismCount: 5,
For the evaluation function, I set it to 0 if there is no humans left.
Any advice ?
My ElitismCount is 10. My MutationRate is higher (15%). I do not have a maxGenerations parameter: I let the search run for the allocated period of time which gives me 3K generations per second for the Rectangle test case. For crossover, I choose randomly between my two populations for each consecutive move.
Given that it is a very simple test case, it should converge with your parameters. Is it your only failed test case ?
Also you could always use a âfallbackâ strategy if your GA doesnât find a solution in the given time period, use a âgreedy(non optimal)â approach.
Thanks for the advices
My simulation engine was wrong.
I update it ==> now GA works for everything but Rectangle test case.
As mentioned, I added a fallback to naive algorithm if GA fails.
I get to 425th
I will try to change my crossover: for now it is a random swapPoint; taking [0:swapPoint] from parent 1 and [swapPoint:end] from parent 2
how to get the position of ash?
itâs given in the first line of every game turn
Iâm trying to get started here so that I can begin my path down the optimization tree of the achievements and Iâm just not sure whatâs already been done, I discussed with somebody in chat today about using beam search and was curious what other peoplesâ thoughts were?
In this thread there are several strategies explained, I personally used GA: Code VS Zombies - Optimization - Puzzle discussion
Look here for some feedback on the strategies used for this puzzle (mostly MonteCarlo and genetic algorithms). Regarding beam search, this is an interesting idea but I see two potential issues:
- given Ash movement freedom, the search space is really huge even if you discretize movements.
- because of the scoring system which favors carnage, good solutions herd zombies first and delay shooting as much as possible, so itâs hard to distinguish the right first moves
Bonjour.
Question, Ash tue les Zombies se trouvant dans un rayon de 2000 ou dans un rayon de moins de 2000 (2000-1) ?
Parce quâil est dit dans lâĂ©noncĂ© :
Si Ă la fin dâun tour, un zombie se trouve dans un rayon de 2000 unitĂ©s de Ash, il tire sur le zombie pour le dĂ©truire
Mais plus loin on a :
Tout zombie se situant dans un rayon de moins de 2000 unités est détruit
Merci
Les zombies qui sont dans un rayon de moins de 2000 de Ash meurent. Câest ce que jâai dans ma simulation et câest cohĂ©rent avec le referee.
Hi Developers,
Could someone tells us more about the validators ?
As far as Iâm concerned, âUnavoidable deathsâ always fails without knowing why
I havenât hard coded anything
Thanks in advance
Hello,
I donât have a really optimized solution (score : 49k) but I had the same issue with the âUnavoidable deathsâ validator that always failed without understanding why. I solved it by sending Ash to save the human who is the closest to a zombie but still can be saved.
I think itâs a good way to save all lives that can be saved but if someone has an other option I am curious, please share it.
Thanks in advance and I hope I could help !
Hi,
Thanks for the hint my friend.
Iâll make the necessary adjustments
help me please
thank you
https://how-to-properly-ask-a-question.surge.sh/
How do you expect to have help without any precision ???
Can someone explain this part of the statement?
I donât understand why a zombie should land on X=282.843, Y=282.843 how can I calculate the new coordinates of zombies?
Thanks.
trigonometry