1. Gabor, T., Illium, S., Zorn, M., et al. 2022. Self-replication in neural networks. Artificial Life 28, 2, 205–223.

Children Evolution

This study extends previous work on self-replicating neural networks, focusing on backpropagation as a mechanism for facilitating non-trivial self-replication. It delves into the robustness of these self-replicators against noise and introduces artificial chemistry environments to observe emergent behaviors. Additionally, it provides a detailed analysis of fixpoint weight configurations and their attractor basins, enhancing the understanding of self-replication dynamics within neural networks. [Gabor et al. 2022]

Noise Levels

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