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Main Author: Dharamdass, Ramesh Lal
Format: Recurso digital
Language:English
Published: Zenodo 2026
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Online Access:https://doi.org/10.5281/zenodo.18916996
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author Dharamdass, Ramesh Lal
author_facet Dharamdass, Ramesh Lal
contents <blockquote> <p>English contains approximately 600,000 documented words, yet everyday communication relies on a core set of roughly 5,000 high‑frequency terms—“less than 1% of the available lexicon.”</p> <p>This work introduces the <strong>Symbolic‑Combinatorial Cognition Theory (SCCT)</strong>, a formal model proposing that human thought is a generative combinatorial process operating primarily over this small daily‑active vocabulary. SCCT integrates linguistic statistics, predictive processing, and symbolic generative models to explain how finite symbolic inventories produce both the richness and the constraints of human cognition. The theory formalizes cognition as a constrained combinatorial search over high‑frequency symbolic units and argues that conceptual granularity, cognitive resolution, and reasoning flexibility scale with the size of the active vocabulary. Implications for cognitive development, education, creativity, and artificial intelligence are explored.</p> </blockquote> <div> </div> <h1> </h1>
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spellingShingle The Symbolic‑Combinatorial Cognition Theory (SCCT): A Formal Model of Human Thought Based on Finite Symbol Sets and Daily Active Vocabulary Constraints
Dharamdass, Ramesh Lal
Symbolic cognition; Combinatorial models; Active vocabulary; Predictive processing; Cognitive resolution; Conceptual granularity; Linguistics; Cognitive science; Artificial intelligence; Generative models
<blockquote> <p>English contains approximately 600,000 documented words, yet everyday communication relies on a core set of roughly 5,000 high‑frequency terms—“less than 1% of the available lexicon.”</p> <p>This work introduces the <strong>Symbolic‑Combinatorial Cognition Theory (SCCT)</strong>, a formal model proposing that human thought is a generative combinatorial process operating primarily over this small daily‑active vocabulary. SCCT integrates linguistic statistics, predictive processing, and symbolic generative models to explain how finite symbolic inventories produce both the richness and the constraints of human cognition. The theory formalizes cognition as a constrained combinatorial search over high‑frequency symbolic units and argues that conceptual granularity, cognitive resolution, and reasoning flexibility scale with the size of the active vocabulary. Implications for cognitive development, education, creativity, and artificial intelligence are explored.</p> </blockquote> <div> </div> <h1> </h1>
title The Symbolic‑Combinatorial Cognition Theory (SCCT): A Formal Model of Human Thought Based on Finite Symbol Sets and Daily Active Vocabulary Constraints
topic Symbolic cognition; Combinatorial models; Active vocabulary; Predictive processing; Cognitive resolution; Conceptual granularity; Linguistics; Cognitive science; Artificial intelligence; Generative models
url https://doi.org/10.5281/zenodo.18916996