Genetic algorithms for training deep neural networks (2017)
1–10 of 23 posts
Re: Genetic algorithms for training deep neural networks (2017)
#2The article is from last year but it's still extremely valuable and interesting.
Exploring this topic is currently my primary hobby. Specifically, I've been using OpenAI's retro (Sonic, Contra, Mario, Donkey Kong and, more recently FZero) and comparing the ancient NEAT with more fashionable stuff like DQN, PPO, A3C and DDPG.
With my extremely limited experience, NEAT seems to outperform all of these other algorithms. I believe the advantage is the potential for strange/novel network structure.
And the best part is that NEAT doesn't require a powerful GPU.
Apologies for the shameless plug but here's a link to a series on youtube I made about using Retro and NEAT together to play Sonic. https://www.youtube.com/watch?v=pClGmU1JEsM&list=PLTWFMbPFsv...
Re: Genetic algorithms for training deep neural networks (2017)
#3I lost it at "emerging revolution".
My PhD thesis in 2000 already used genetic algorithms for seeds and it was hardly new then.
Re: Genetic algorithms for training deep neural networks (2017)
#4I lost it at "emerging revolution". My PhD thesis in 2000 already used genetic algorithms for seeds and it was hardly new then.
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Re: Genetic algorithms for training deep neural networks (2017)
#5I lost it at "emerging revolution". My PhD thesis in 2000 already used genetic algorithms for seeds and it was hardly new then.
I had a genetically trained neural network driving a car simulation* in qbasick in 1997, and it wasn't "novel" it was quite common back then to combine them.
*a very limited one, imagine 2d, no inertia, 5 sensors at 15° each other each reporting distance from the nearest "grass", with the road 20px wide, drawn by hand gray on green and fitting the screen 13 space. network was 5x5 neuron, with weights all part of the gneetic code. car never made past the fourth corner, let alone did a lap.
Re: Genetic algorithms for training deep neural networks (2017)
#6step 1: hook it up to a car
Re: Genetic algorithms for training deep neural networks (2017)
#7I lost it at "emerging revolution". My PhD thesis in 2000 already used genetic algorithms for seeds and it was hardly new then.
Genetic algorithms are (and were already back in 2000) a pretty decent and -more importantly- generic solution to the problem of global optimization (as opposed to local optimization) when the problem to optimize has some sort of (maybe not-so-smooth) structure.
Many of the recent "AI" development very often boil down to finding a local extremum using some sort of ski down the slope optimization program (aka "training"). These techniques very rarely tackles global optimization, or when they do, bundle it up under the moniker "hyper-parameter tuning".
A good example of something that falls under "global optimization" and isn't often tackled in deep learning would be finding the correct deep net architecture for a given problem.
The problem doesn't lend itself very well to local optimization, but might yield to GA-type optimization.
Re: Genetic algorithms for training deep neural networks (2017)
#8For those interested, i built a python app on top of tensorflow/keras to do neural networks architecture & hyper parameters search with genetic algorithms.
Re: Genetic algorithms for training deep neural networks (2017)
#9For those interested, i built a python app on top of tensorflow/keras to do neural networks architecture & hyper parameters search with genetic algorithms. https://github.com/guybedo/minos
Note that here the weights are evolved, not just the parameters. Gradient descent is not used at all AFAIK.
Re: Genetic algorithms for training deep neural networks (2017)
#10This is a fun book (published in 2001) about how a professor and his graduate assistant developed a world-class checkers-playing algorithm using neuroevolution:
https://en.wikipedia.org/wiki/Blondie24
https://www.amazon.com/Blondie24-Playing-Kaufmann-Artificial...
(Edit) One of the funniest parts I remember is that they had to leave it running on a Pentium III for like a month or something.