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Quantum Analogical Modeling (QAM) works under the assumption that the correctexemplar-based description for a system of behavior minimizes the overalluncertainty of the system. The measure used in QAM differs from the traditionallogarithmic measure of uncertainty; instead QAM uses a quadratic measure ofdisagreement between pairs of exemplars. (This quadratic measure parallels thesquaring function holding between the amplitude and the probability for a statefunction in quantum mechanics.) QAM eliminates all supracontexts (contextualgroupings of exemplars) that fail to minimize the number of disagreements. Theresulting system thus distinguishes between homogeneous and heterogeneoussupracontexts and uses only exemplars in homogeneous supracontexts to predictbehavior. This paper revises earlier work on QAM (in 2005) by showing thathomogeneity for a supracontext can be most simply determined by discoveringwhether there are any heterogeneous pointers between any of the supracontext'sexemplars. A pointer for a pair of exemplars is heterogeneous whenever thosetwo exemplars are found in different subcontexts of the supracontext and takedifferent outcomes.

Quantum Analogical Modeling with Homogeneous Pointers