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From Simple Machines to Eureka in Four Not-So-Easy Steps: Towards Creative Visuospatial Intelligence

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Fundamental Issues of Artificial Intelligence

Part of the book series: Synthese Library ((SYLI,volume 376))

Abstract

This chapter builds an account of the cognitive abilities and mechanisms required to produce creative problem-solving and insight. Such mechanisms are identified in an essentialized set of human abilities: making visuospatial inferences, creatively solving problems involving object affordances, using experience with previously solved problems to find solutions for new problems, generating new concepts out of old ones. Each such cognitive ability is selected to suggests a principle necessary for the harder feat of engineering insight. The features such abilities presuppose in a cognitive system are addressed. A core set of mechanisms able to support such features is proposed. A unified system framework in line with cognitive research is suggested, in which the knowledge-encoding supports the variety of such processes efficiently.

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Notes

  1. 1.

    Several different proposals which aim to summarize all macro-narratives exist, a compelling one being offered by Booker (2004), however for a computational treatment of micro narrative schemas see Chambers and Jurafsky (2010). In the context of insight, the established narrative schema could be about inspiration that comes to the discoverer after a lot of work in a spontaneous flash, in which various parts of the problem are “perceived” together with similar inspiration-conducive objects.

  2. 2.

    This can hold true only if the imagery which accompanies insight is real and in direct relation to the causal processes of insight – i.e. visual imagery is perceived because visual components of concepts are activated and worked upon with visual and other processes in order to propose a solution.

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Acknowledgements

The work reported in this chapter was conducted in the scope of the project R1-[Image-Space] of the Collaborative Research Center SFB/TR8 Spatial Cognition. Funding by the German Research Foundation (DFG) is gratefully acknowledged.

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  1. Universität Bremen, Enrique-Schmidt-Str. 5, 28359, Bremen, Germany

    Ana-Maria Olteţeanu

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  1. Ana-Maria Olteţeanu
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Correspondence to Ana-Maria Olteţeanu .

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Editors and Affiliations

  1. Future of Humanity Institute Department of Philosophy & Oxford Martin School, University of Oxford, Oxford, UK

    Vincent C. Müller

  2. Anatolia College/ACT, Thessaloniki, Greece

    Vincent C. Müller

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Olteţeanu, AM. (2016). From Simple Machines to Eureka in Four Not-So-Easy Steps: Towards Creative Visuospatial Intelligence. In: Müller, V.C. (eds) Fundamental Issues of Artificial Intelligence. Synthese Library, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-26485-1_11

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