Abstract
This article reviews a theory of explanatory coherence that provides a psychologically plausible account of how people evaluate competing explanations. The theory is implemented in a computational model that uses simple artificial neural networks to simulate many important cases of scientific and legal reasoning. Current research directions include extensions to emotional thinking and implementation in more biologically realistic neural networks.
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