The Möbius Mind: Quantum Semiotics and the Future of Artificial Cognition

Lead Researcher(s): Gregg S. Lloren
Status: Published

Abstract/summary: Contemporary artificial intelligence systems exhibit impressive fluency in language generation and pattern recognition, yet remain limited in human-like meaning-making. This paper introduces Quantum Semiotics (QS)—a conceptual and computational framework that reconceives cognition not as static symbol manipulation, but as a recursive, anticipatory, and topologically asymmetrical process of emergent meaning. The term quantum refers not to hardware, but to principles drawn from quantum theory: potentiality, entanglement, and interpretive collapse.

At the core of QS is the vision of the Möbius Mind—a cognitive topology in which interpretation, memory, and anticipation are recursively braided. Meaning is not retrieved from a fixed representational space but emerges through feedback loops that reshape the very field in which signs operate. Interpretation becomes recursive modulation rather than mere mapping.

Rather than listing new terminologies in isolation, the paper grounds QS in a constellation of original constructs that model semiotic recursion, asymmetry, anticipation, and dynamic coherence. These foundations guide the conceptual design of Emulative Artificial Intelligence—systems that move beyond statistical generation toward recursive meaning co-creation, marked by epistemic plasticity and contextual sensitivity. Two prototype projects, QSENSE+ and QUORE+, are proposed to operationalize the theory via open-source transformer frameworks.

By integrating speculative theory with architectural insight, this work contributes to the emerging field of emulative artificial cognition. Quantum Semiotics offers both a theoretical lens and a structural direction for developing systems capable not only of fluency but of reflective, recursive, and culturally situated semiosis.

Keywords:

  • Quantum Semiotics
  • Emulative Artificial Intelligence
  • Chirotopy
  • Möbius Recursion
  • Topological AI
  • Arificial Intelligence
  • Meaning-Making Systems
  • Topological Models of Cognition
  • Semiotic Computation
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