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MEASURING INTELLIGENCE QUOTIENTS OF HYBRID HUMAN–MACHINE–AI SYSTEMS A Categorical and Measurement-Theoretic Framework
We develop a mathematically explicit framework for measuring the intelligence of hybrid systems composed of human, conventional-machine, and artificial-intelligence (AI) agents. Agents and environments are modeled as morphisms in a Markov category, so that the law of an interaction history,
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