Is Holism A Problem For Inductive Inference? A Computational Analysis

Maxwell A. BertoleroHelen Wills Neuroscience Institute, University of California, Berkeley
Maxwell A. BertoleroDepartment of Psychology, University of California, Berkeley
Tom L. GriffithsHelen Wills Neuroscience Institute, University of California, Berkeley
Tom L. GriffithsDepartment of Psychology, University of California, Berkeley

Abstract

We investigate whether holism presents a problem for inductive inference by examining the relationship between the size of a Bayesian network that represents human conceptual knowledge and the computational complexity of probabilistic inference in that network. We find that, despite prior claims, holism may not be a problem for inductive inference, as computational cost does not increase exponentially as the network grows. While the network we analyze is holistic, it has a modular organization and grows in a way that potentially makes efficient inductive inference possible.

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