Integrated World Modeling Theory (IWMT) and the Human Consciousness Hypothesis (HCH)

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Authors: Adam Safron, Victoria Klimaj, Zahra Sheikhbahaee
Cited by: 1

Abstract

Here, we explore points of convergence between the Human Consciousness Hypothesis (HCH) and Integrated World Modeling Theory (IWMT). HCH posits that consciousness is defined by three fundamental principles: Genesis (conscious functions constituting an early-stage learning algorithm), Coherence (maximization of representational consistency), and Second-Order Perception (synchronous meta-awareness of perceptual processes). IWMT serves as a unifying model that reconciles major theories of consciousness with a particular focus on Global Neuronal Workspace Theory, Integrated Information Theory, and the Free Energy Principle and Active Inference framework. Central to IWMT is the proposal that phenomenal consciousness is “what it feels like” to be the spatiotemporally and causally coherent functioning of a probabilistic generative world model for an embodied agent. Mechanistically, IWMT identifies "self-organizing harmonic modes" (SOHMs) as synchronous neural complexes implementing iterative Bayesian inference to generate consciousness as maximum a posteriori estimates of embodied sensorium states. Nested heterarchies of SOHMs are proposed as biophysical substrates for consciousness, acting as dynamic cores of integrated information that facilitate the synchronous combination of multimodal sense data into a unified field of experience to promote intelligent/adaptive (active) inference and learning. Critically, IWMT requires (body-)world models to be capable of both informing and being informed by action-perception cycles at behaviorally relevant timescales. This architecture suggests consciousness could potentially be realized in artificial systems with appropriate recurrent dynamics and sufficient degrees (and kinds) of embodied grounding.

Fields of Study & Subjects

Embodied and Extended Cognition Philosophy and Theoretical Science Cognitive Science and Education Research

Publication details

Journal / source
Proceedings of the AAAI Symposium Series
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Volume
8
Issue
1
Pages
345–351
Publication date
18 May 2026
Language
EN