Consciousness as a Functor
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Abstract (arXiv)
We propose a novel theory of consciousness as a functor (CF) that receives and transmits contents from unconscious memory into conscious memory. Our CF framework can be seen as a categorial formulation of the Global Workspace Theory proposed by Baars. CF models the ensemble of unconscious processes as a topos category of coalgebras. The internal language of thought in CF is defined as a Multi-modal Universal Mitchell-Benabou Language Embedding (MUMBLE). We model the transmission of information from conscious short-term working memory to long-term unconscious memory using our recently proposed Universal Reinforcement Learning (URL) framework. To model the transmission of information from unconscious long-term memory into resource-constrained short-term memory, we propose a network economic model.
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References · 12
- 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
- 2017The Consciousness Priorcited by 107
- 2019A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statisticscited by 56
- 2017Disintegration and Bayesian Inversion via String Diagramscited by 32
- 2021An enriched category theory of language: from syntax to semanticscited by 22
- 2021A Theory of Consciousness from a Theoretical Computer Science Perspective: Insights from the Conscious Turing Machinecited by 22
- 2022The d-separation criterion in Categorical Probabilitycited by 12
- 2020A Theoretical Computer Science Perspective on Consciousnesscited by 8
- 2021Universal Decision Modelscited by 7
- 2017Incremental constraint projection methods for monotone stochastic variational inequalitiescited by 3
- 2024Universal Imitation Gamescited by 2
- 2025Universal Reinforcement Learning in Coalgebras: Asynchronous Stochastic Computation via Conductioncited by 2
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