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arXiv AI By Simon Hegelich, Bardh Prenkaj, Habiba Sarhan, Morteza Shahrezaye, Kolja Hegelich, Erik Cambria, Christian Montag

Co-Recursive Semantic Self-Extension: A Mathematical Foundation for Open-Ended Intelligence

Read the original on arXiv AI →

The paper argues that current AI systems are limited by their fixed representational frameworks and that true open‑ended intelligence requires the ability to extend its own semantic domain. By modeling cognitive states as partial evaluations over a formal language, the authors show that unresolved propositions create a frontier for extension that cannot be fully resolved by finite architectures. They propose that intelligence must transform unresolved structures into new spaces of meaning—generating new distinctions, questions, representations, and purposes—through persistent external memory and collective generative capacity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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