Synthetic Concept Evolution Under the Axiom of Truth
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902215904460800 |
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| author | Rubendall, C. Mike "WildFacts" |
| author_facet | Rubendall, C. Mike "WildFacts" |
| contents | <p>We propose and test a protocol for automated conceptual evolution using random-<br>ized grammatical generation filtered through the Axiom of Truth (AoT). The AoT<br>acts as a survival function ensuring that only self-consistent statements persist. The<br>experiment demonstrates that conceptual novelty and structural integrity can arise<br>spontaneously from grammatical randomization when filtered by causal–logical con-<br>straints. The process mimics natural selection, substituting logical consistency for<br>biological fitness.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17282853 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Synthetic Concept Evolution Under the Axiom of Truth Rubendall, C. Mike "WildFacts" Artificial intelligence Artificial Intelligence Artificial Intelligence/standards Artificial Intelligence/classification Artificial Intelligence/ethics Artificial Intelligence/statistics & numerical data <p>We propose and test a protocol for automated conceptual evolution using random-<br>ized grammatical generation filtered through the Axiom of Truth (AoT). The AoT<br>acts as a survival function ensuring that only self-consistent statements persist. The<br>experiment demonstrates that conceptual novelty and structural integrity can arise<br>spontaneously from grammatical randomization when filtered by causal–logical con-<br>straints. The process mimics natural selection, substituting logical consistency for<br>biological fitness.</p> |
| title | Synthetic Concept Evolution Under the Axiom of Truth |
| topic | Artificial intelligence Artificial Intelligence Artificial Intelligence/standards Artificial Intelligence/classification Artificial Intelligence/ethics Artificial Intelligence/statistics & numerical data |
| url | https://doi.org/10.5281/zenodo.17282853 |