Imagination as General Intelligence: Reconciling Consciousness and Free Will with Modern Physics
Authors/Creators
Description
Version 3.0 — Qualia Reframed: This update clarifies Section 7.1 by addressing the “Hard Problem of Consciousness.” Qualia are reframed as functional data formats — integrated, value-tagged summaries that allow rapid comparison of predicted timelines. This dissolves qualia as a philosophical impasse and grounds the framework in testable, evolutionary, and computational mechanisms.
This white paper introduces the Predictive Timeline Simulation (PTS) Framework, a model that reframes consciousness as an evolved predictive simulation engine. Drawing on neuroscience, predictive processing, and the Block Universe model of spacetime, it offers a functional, testable account of consciousness without resorting to mysticism.
The framework has implications across multiple domains:
-
Philosophy: Proposes an evolutionary role for qualia, treating them as a data format for navigating a deterministic universe.
-
Neuroscience: Models how the brain’s “common core network” and predictive systems create a workspace for simulating and evaluating future timelines.
-
Clinical Science: Introduces the Simulation Misfiling Hypothesis, suggesting schizophrenia may result from a breakdown in executive control over this simulation process, with implications for early detection and intervention.
-
Artificial Intelligence: Outlines a blueprint for Artificial General Intelligence (AGI) grounded in imagination — the ability to simulate novel futures as the true engine of general intelligence.
Grounded in physics and evolution, this paper presents a unified, testable framework with clear implications for philosophy, neuroscience, clinical science, and AI research, supported by a robust multidisciplinary bibliography.
Files
5D_Consciousness_White_Paper (11).pdf
Files
(3.2 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:099727e719c3ef5478db1a2017c7959d
|
3.2 MB | Preview Download |
Additional details
Dates
- Submitted
-
2025-09-12Submitted version of white paper for public access
- Available
-
2025-09-12ubmitted version of white paper for public access