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# Examples & Use Cases
It would be great if we could get a strong set of use cases and examples built out for different communities to be able to use in their individual projects - and maybe add th…
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Getting the following errors from a fresh git clone following README instructions:
SIDE NOTE: I'm installing this on an Ubuntu OS using Windows Subsystem for Linux
```
(env) nostrademous@DESKTOP-J9…
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The seed repeats itself. A good eample is https://raw.githubusercontent.com/neuroevolution-ai/CTRNN_Simulation_Results/master/evaluation/bamemory/ctrnn/2021-02-23_05-18-06/Log.txt
Every 36 generati…
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I know you linked to the article regarding the algorithm but it would be useful to have a walk-through (high-level) of what the Neuroevolution is doing in the case of this game.
For example, talkin…
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add boolean option to episoderunnner.
if true, than then add the last fitness to next observation for the brain.
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```
What steps will reproduce the problem?
1.training mode
2.add new qlearning / neuroEvolution team
3.save/load
What is the expected output? What do you see instead?
I expect a file save with the …
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This issue is not a specific todo. It's a place to gather idea for optimizers to implement next
https://github.com/ShawK91/Evolutionary-Reinforcement-Learning
ERL sieht sehr relevant aus. Wir …
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Our current brain hierarchy of the PyTorch brains is a little bit cluttered. While the PyTorch implementations of Elman, GRU and LSTM use `IPytorchBrain` as a base class, the FFNN PyTorch implementati…
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```
What steps will reproduce the problem?
1.training mode
2.add new qlearning / neuroEvolution team
3.save/load
What is the expected output? What do you see instead?
I expect a file save with the …
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TL;DR:
Fitness of individuals is decided by their rank in their generation but not by their rank across generations
In each generation after the training episodes are done we do the following:
…