Consciousness as a Functor

TL;DR

This paper introduces a categorical framework for consciousness as a functor, integrating global workspace theory with novel models of information transmission between unconscious and conscious memory using advanced mathematical structures.

Contribution

It presents a new theoretical model of consciousness as a functor within category theory, combining topos categories, a universal language, and reinforcement learning to explain information flow.

Findings

CF models unconscious processes as a topos category

Introduces MUMBLE as a language for thought

Proposes network economic model for memory transmission

Abstract

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.