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2025
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| Online Access: | https://doi.org/10.5281/zenodo.16744131 |
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| author | Ryan David Oates, Ryan David Oates |
| author_facet | Ryan David Oates, Ryan David Oates |
| contents | <p>v1.1 Removes Inaccurate association with University of California, Santa Barbara research department. </p> <p><br>Framework (UPOF)<br>Ryan Oates∗, with contributions from Claude Sonnet 4† and Grok 4 Expert‡<br>∗Jumping Quail Solutions <br>†‡Anthropic & xAI<br>Email: ryan oates@my.cuesta.edu<br>Abstract—This paper introduces the Unified Onto-<br>Phenomenological Consciousness Framework (UPOF), a<br>novel theoretical and computational architecture designed to<br>model and quantify consciousness. The UPOF integrates a<br>cognitive process ontology with the Transcendent-Omega-Hyper-<br>Meta-Reconstruction framework, defining core mathematical<br>constructs, operational citadels, and a dialectical synthesis<br>process. We present the central equations governing the<br>framework, including a cognitive-memory distance metric,<br>an emergence functional, and a core consciousness equation<br>that balances symbolic and neural processing streams. The<br>framework’s utility is demonstrated through diverse applications,<br>from solving International Mathematical Olympiad (IMO)<br>problems to analyzing chaotic systems and correcting cognitive<br>biases in complex data interpretation. This work aims to bridge<br>the explanatory gap between the ontological foundations and<br>the phenomenological dynamics of consciousness, providing a<br>tractable, rigorous, and empirically testable model.<br>Index Terms—computational consciousness, cognitive mod-<br>eling, metric spaces, neural-symbolic integration, emergence,<br>dynamic systems theory, machine learning, UPOF.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16744131 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
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| spellingShingle | The Unified Onto-Phenomenological Consciousness Framework (UPOF) Ryan David Oates, Ryan David Oates <p>v1.1 Removes Inaccurate association with University of California, Santa Barbara research department. </p> <p><br>Framework (UPOF)<br>Ryan Oates∗, with contributions from Claude Sonnet 4† and Grok 4 Expert‡<br>∗Jumping Quail Solutions <br>†‡Anthropic & xAI<br>Email: ryan oates@my.cuesta.edu<br>Abstract—This paper introduces the Unified Onto-<br>Phenomenological Consciousness Framework (UPOF), a<br>novel theoretical and computational architecture designed to<br>model and quantify consciousness. The UPOF integrates a<br>cognitive process ontology with the Transcendent-Omega-Hyper-<br>Meta-Reconstruction framework, defining core mathematical<br>constructs, operational citadels, and a dialectical synthesis<br>process. We present the central equations governing the<br>framework, including a cognitive-memory distance metric,<br>an emergence functional, and a core consciousness equation<br>that balances symbolic and neural processing streams. The<br>framework’s utility is demonstrated through diverse applications,<br>from solving International Mathematical Olympiad (IMO)<br>problems to analyzing chaotic systems and correcting cognitive<br>biases in complex data interpretation. This work aims to bridge<br>the explanatory gap between the ontological foundations and<br>the phenomenological dynamics of consciousness, providing a<br>tractable, rigorous, and empirically testable model.<br>Index Terms—computational consciousness, cognitive mod-<br>eling, metric spaces, neural-symbolic integration, emergence,<br>dynamic systems theory, machine learning, UPOF.</p> |
| title | The Unified Onto-Phenomenological Consciousness Framework (UPOF) |
| url | https://doi.org/10.5281/zenodo.16744131 |