28 lines
3.0 KiB
Plaintext
28 lines
3.0 KiB
Plaintext
---
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title: "Extended Self-Replication"
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tags: [artificial-life, complex-systems, neural-networks, self-organization, dynamical-systems, self-replication, emergent-behavior, robustness, replication-fidelity]
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excerpt: "Journal extension: self-replication, noise robustness, emergence, dynamical system analysis."
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teaser: "/figures/15_sr_journal_teaser.jpg"
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venue: "Artificial Life 28 (2022)"
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---
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<FloatingImage src="/figures/15_sr_journal_teaser.jpg" alt="Scatter plot showing the relationship between relative parent distance and replication outcome or child distance" width={600} height={480} float="right" caption="An analysis of replication fidelity, showing how the distance between parent and child networks relates to different parent distances." />
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This journal article <Cite bibtexKey="gabor2022self" /> provides an extended and more in-depth exploration of self-replicating neural networks <Cite bibtexKey="gabor2019self" />, building upon earlier foundational work ([Gabor et al., 2019](link-to-previous-paper-if-available)).
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The research further investigates the use of **backpropagation-like mechanisms** not for typical supervised learning, but as an effective means to enable **non-trivial self-replication** – where networks learn to reproduce their own connection weights.
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<CenteredImage src="/figures/15_sr_journal_children.jpg" alt="Visualization showing the evolution or diversity of 'child' networks generated through self-replication" width={600} height={300} caption="Analyzing the lineage and diversity in populations of self-replicating networks." />
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Key extensions and analyses presented in this work include:
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* **Robustness Analysis:** A systematic evaluation of the self-replicating networks' resilience and stability when subjected to various levels of **noise** during the replication process.
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* **Artificial Chemistry Environments:** Further development and analysis of simulated environments where populations of self-replicating networks interact, leading to observable **emergent collective behaviors** and ecosystem dynamics.
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* **Dynamical Systems Perspective:** A detailed theoretical analysis of the self-replication process viewed as a dynamical system. This includes identifying **fixpoint weight configurations** (networks that perfectly replicate themselves) and characterizing their **attractor basins** (the regions in weight space from which networks converge towards a specific fixpoint).
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<CenteredImage src="/figures/15_noise_levels.jpg" alt="Graph showing the impact of different noise levels on self-replication fidelity or population dynamics" width={600} height={450} caption="Investigating the influence of noise on the self-replication process." />
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By delving deeper into the mechanisms, robustness, emergent properties, and underlying dynamics, this study significantly enhances the understanding of how self-replication can be achieved and analyzed within neural network models, contributing valuable insights to the fields of artificial life and complex systems. |