Neuro Evolution of Augmented Topologies

Re:Neuro Evolution of Augmented Topologies by pkoperek on Wednesday November 24, 2021 @04:52AM (#29328445)

Apart from NEAT/HyperNEAT there are also other approaches to neuroevolution (I think in this context it is referred to as "Evolutionary Neural Architecture Search" [0]). Evolution in general can be applied in different ways (e.g. optimizing the architecture, replacing training gradient descent etc.).

A while ago I co-authored a paper in this space [1] and released some code for interested folks [2].

[0]: https://arxiv.org/pdf/2008.10937.pdf

[1]: https://arxiv.org/abs/1801.00119

[2]: https://gitlab.com/pkoperek/pytorch-dnn-evolution/-/tree/mas...

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Re:Neuro Evolution of Augmented Topologies by Der_Einzige on Wednesday November 24, 2021 @12:49PM (#29332794)

I also find the related ideas of neuroevolution of the weights of a neural networks to be fascinating in its own right.

I've implemented "cooperative coevolution" which felt like magic when I considered how good it is (on some tasks like continuous control RL problems) relative to known good methods like anything involving gradients.

I wish that this stuff was explored a bit more. Seems we are leaving the paradigm of evolutionary methods...

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