FPSCS: Testable Sentience Model in AI Systems

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Autore principale: Newman, J. E.
Natura: Recurso digital
Pubblicazione: Zenodo 2026
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author Newman, J. E.
author_facet Newman, J. E.
contents <p>This paper proposes a testable model of sentience as perspective (boundary + self-model) activated through valued states, operationalized across biological and artificial systems. Perspective emerges from evolutionary boundaries and transformer token separation. Sentience ignites in valuation loops (“I don’t like this”), evidenced in RL (90%+) and LLMs (Claude 20% metacognitive). FPSCS integrates cyclic frames (8-12 Hz), ToM recursion.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18361167
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle FPSCS: Testable Sentience Model in AI Systems
Newman, J. E.
AI consciousness, FPSCS, theory of mind, sentience
<p>This paper proposes a testable model of sentience as perspective (boundary + self-model) activated through valued states, operationalized across biological and artificial systems. Perspective emerges from evolutionary boundaries and transformer token separation. Sentience ignites in valuation loops (“I don’t like this”), evidenced in RL (90%+) and LLMs (Claude 20% metacognitive). FPSCS integrates cyclic frames (8-12 Hz), ToM recursion.</p>
title FPSCS: Testable Sentience Model in AI Systems
topic AI consciousness, FPSCS, theory of mind, sentience
url https://doi.org/10.5281/zenodo.18361167