A New Computational Framework for Predictive Discovery and Latent Behavioral Dynamics

The World Engine proposes a computational framework for discovery systems that model evolving behavioral states rather than relying solely on history, language, and fixed user personas. Drawing on research across artificial intelligence, neuroscience, decision science, and recommender systems, the paper introduces Signal Intelligence, Archetypes, Digital Minds, and World State as testable components of a predictive discovery architecture.

The framework is presented as a research hypothesis and an experimental program. Its central claims remain subject to simulation, controlled evaluation, and testing with real users.

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