Abstract
The general objective is to consider how the use of visual mental imagery in thinking may be relevant to hypothesis generation. There has been little research into the possibility of visual and imagery representations of hypotheses, despite abundant reports (e. g. Einstein and Faraday) that imaging is crucial to scientific discovery. Some hypotheses naturally take a pictorial form: the hypothesis that the earth has a molten core might be better represented by a picture that shows solid material surrounding the core. We will discuss the particular computational imagery representation scheme proposed by Glasgow and Papadias. They have suggested an interesting technique for combining image-like representations and processing with linguistic information. The system they describe can make inferences using such cognitive representations as visual mental imagery ones. It seems to have some of the characteristics of Johnson-Laird’s mental representations - achieving conclusions without laborious chains of inferences. We plan to explore whether this kind of hybrid imagery/linguistic representation can be improved and used to model image-based hypothesis generation, that is to delineate the first features of what we call visual abduction.
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Magnani, L., Civita, S., Massara, G.P. (1994). Visual Cognition and Cognitive Modeling. In: Cantoni, V. (eds) Human and Machine Vision. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1004-2_16
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DOI: https://doi.org/10.1007/978-1-4899-1004-2_16
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