Author: Allen Proxmire
Last Updated: December 2025
Regulated Multiplicity is a theoretical framework proposing that consciousness arises from the regulated interaction of multiple semi‑independent internal models. Rather than treating subjectivity as an unexplained accompaniment to cognition, the framework identifies conscious experience with the internal standpoint generated by adjudicating among competing interpretations, predictions, evaluations, and action proposals.
This repository contains:
- Full manuscripts
- A short note
- A one‑page explainer
- Supporting materials and conceptual diagrams (as they are added)
The goal is to make the theory accessible to researchers, philosophers, cognitive scientists, and anyone interested in the architecture of mind.
The central hypothesis:
Consciousness is the internal perspective generated by a system that must regulate disagreement among its own semi‑independent internal models.
Cognitive systems maintain multiple processes—perceptual hypotheses, predictive models, evaluative routines, motor plans, narrative framings—that generate competing answers to internally posed questions. Consciousness is the standpoint from which these alternatives are compared, weighed, revised, and sometimes suppressed.
Multiplicity provides the raw material.
Regulation provides coherence.
Subjectivity is the internal aspect of this regulatory process.
Cognition is inherently plural. Systems maintain multiple semi‑independent internal models that differ in content, weighting, and evaluative stance.
Cognitive systems ask internal questions that suspend immediate commitment and solicit alternatives. This creates a functional space for deliberation.
Four mechanisms construct coherence:
- Gating
- Binding
- Accountability
- Persistence
Consciousness is the internal perspective of the regulatory process that adjudicates among competing internal models.
Regulated Multiplicity provides a unified architectural explanation for:
- Subjectivity
- The continuum of consciousness
- Developmental changes (e.g., childhood slow time)
- Pathology (e.g., schizophrenia, OCD, dissociation)
- Why current AI systems lack consciousness
- A reframing of the hard problem
The framework is compatible with predictive processing, global workspace theories, and self‑model theories, but offers a distinct architectural emphasis.
/manuscript/ Full polished long‑form paper /short-note/ 1,000–2,500 word short note /one-pager/ One‑page explainer /philpapers/ Manuscript submitted to PhilPapers.org
More materials will be added over time, including diagrams, talks, and supplementary explanations.
This repository is archived and versioned via Zenodo and hosted on GitHub.
This project is released under the MIT License.
Feel free to use, modify, and build upon the ideas with attribution.