How do you guys fine tune your genetic algorithms? I think my

I take them to a walk through Pripyat, if I need more extreme mutations I slap them on the ass and order them to enter the concrete sarcophagus of chernobyl

>>59449247
>>>/sci/

>>59449288
I forgot /g/ is just comparing consumer products

>>59449247
To the best of my understanding crossover is also useful for escaping local maxima.

>>59449344
damn, thats what I was afraid of. I don't have a lot of wiggle room when it comes to the data type my chromosomes are encoded in, so i'm trying to avoid having to implement crossover as it would be a bitch to implement

>>59449380
Run the test many times with slightly different initial conditions and compare final generation solutions, this might help reveal local maxima

>>59449380

What sort of data type are you using? Not Gray code?

>>59449493
Thanks, I'm starting with randomized inputs so hopefully it won't converge too soon.
>>59449905
The genetic info is encoded in a text file (.ASC) that gets programmed into an fpga.

>>59449247
I create a genetic algorithm that sorts best parameters for my genetic algorithm.

>>59450019

I think we need more info about whatever project you're working on to give you helpful feedback.

>>59450056
How do you sort the best parameters for that one?

>>59450056
Fuck
>>59450120
It's a genetic algorithm that controls the bitstream of an FPGA that should be able to perform some function based on relating the inputs to the outputs. I can give more specifics if you need it but there is a lot of info.

>>59450244

And you're wondering if implementing crossover is worthwhile?

>>59450425
Exactly, after getting the mutation rate correct, all I have to do is button up my fitness calculator, but I couldn't do a crossover and I'm wondering if I can do without it.

>>59450547
>but I couldn't do a crossover
For what reason?

what are your favourite languages for genetic algorithms?

>>59451259
Matlab was always comfy

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>>59449288

go fuck yourself

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What's the point of doing crossover even? Isn't it just a form of mutation.

>>59451248
Because I'm a dummy and the fact that the data has to be encoded in a text file is limiting.
>>59451259
I did mine with python because it's all I know. It sucks for this though.
>>59452089
The way I understand it is that it is a way of combining chunks of mutations so that the beneficial genes will appear sooner and be more rigorous. Could be wrong though.

>>59452505
Please tell me you at least included elitism

>>59452505
>python
>genetic algorithms

OP, you're limiting yourself by using python. Use matlab or some other language akin to it that's more suited for the job.

Crossovers allow for a faster evolution of both beneficial and harmful mutations by mimicking real-world genetic conditions.

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People who use GAs have absolutely no idea what they are doing

You've essentially got a really shitty search algorithm and you'd be better with literally anything else

People think "HURR DURR GENES LIKE HUMAN SO COMPUTAH NOW HUMAN"

It's doesn't work like that tim

Solving problems needs insight of how to best solve the problem and then running the routine to solve it. A GA is never the best way to solve a problem, there is always a better way.

People who like to sound cool use them
And also I notice people shit at math use them because they are easy to use and math is hard for them

Either tell us the details of your fitness calculation or fuck off. It's literally the only thing that matters. The fact ur obsessing over shit like mutation rates and crossover and saying stupid shit like "population size dialled in" like a nig from CSI shows you are a /v/ kiddie.

>>59452568
What's wrong with python? PyEvolve is a very potent library, Deap as well.

>>59452639
>>59449247
OP just got roasted

>>59452639
>A GA is never the best way to solve a problem, there is always a better way.

Eh, depends. Obviously you wouldn't do a GA unless you had a good reason to. Sometimes you have to fit a model in a 500 dimensional parameter space, you have no access to Jacobians or Hessians, and you don't want to get stuck in the first local minimum you find. And sometimes you don't even know which initial parameter set to pick.

>>59449247
Annealing and a separate routine to apply large mutations when peaks are detected

>>59452686
which is why random is usually better at that point

>>59452726

Errr, correct me if I'm wrong - but wouldn't a pure random search be a little bit more costly than a GA solution?

>>59452532
No, but that seems like it might be beneficial once the fitness progresses far enough.
>>59452568
I'm realizing that, but I might be too far in. As long as I get good results without crossover I'm going to stick with what I have
>>59452639
if there is an easier way to deal with almost a million different variables I'd love to hear it.

>>59452686
>>59452801

Another advantage of GAs is that they can handle discrete variables. No calculus needed.

>>59452801
>almost a million different variable.
You don't have a search space. Stop using a GA now you nimwit. GAs are NOT meant for that.

>>59452961
What are you talking about? GAs are meant to tackle problems with high-dimensional parameter spaces.

>>59452961
I don't see why a large chromosome size means I have no search space, but if there is an easier way too do this that nitwit like me could do, I would love to hear about it.

GAs are invented by god, using them is blasphemy, man playing god.
Enjoy the burning fire pits of hell op.

>>59453123
Thanks I will

>>59452686
I've almost finished Calc III and I don't like the implication that I might need to remember about things like hessians and jacobians in a programming related job.

>>59449247
There's a reason nobody's used genetic algorithms for over 2 decades and they were out of style even 4 decades ago.

>>59452686
GAs are literally the last thing you should use for any non-convex optimization problem. They literally get stuck on every single local minimum but also happen to be outrageously unstable.