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MCR-10 develops a framework for reconstructing cognitive models from historical decisions, suggesting new avenues for understanding cognition.
This paper introduces MCR-10 (Mathematical Cognitive Reconstruction), a constraint-based framework for reconstructing feasible cognitive models from historical decisions. Unlike psychological or probabilistic approaches, MCR-10 does not attempt to recover a true cognitive architecture or infer unobservable mental states. Instead, it decomposes decisions into evidence-anchored constraints and reconstructs the set of all deterministic cognitive functions consistent with those constraints. Determinism is treated as a modeling stance rather than an empirical claim, and non-uniqueness is acknowledged asirreducible. MCR-10 outputs a minimal, time-bounded feasible set of cognitive models, providing a reproducible, mathematicallygrounded methodology for computational historical cognition.
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Usman Zafar (2026) studied this question.
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