Abstract
Computational models of novel concept understanding and creativity are addressed in this paper from the viewpoint of conceptual blending theory (CBT). In our approach, a novel, unknown concept is addressed in a communication setting, where this novel concept, created as a blend by an emitter agent, sends a communicative object (words, or in this paper, a visual representation of that concept) to another agent. When received by a computational agent, a novel concept for that communicative object can only be understood by blending concepts already known by that agent. In this paper, we first posit that understanding new concepts via blending is also a creative process. Albeit different from generating conceptual blends, understanding a novel concept via blending involves the disintegration and decompression of that novel concept, in such a way that the receiver of that concept is able to re-create the conceptual network supposedly intended by the emitter of the novel concept. Secondly, we also propose image schemas as a tool that agents can use to interpret the spatial information obtained when disintegrating/unpacking novel concepts and then re-create the new blend. This process is studied in a communication setting where semiotics and meaning are conveyed by visual and spatial signs (instead of the usual setting of natural language or text). In this case study, qualitative spatial descriptors are applied for obtaining a formal description of an icon or pictogram, which is later assigned a meaning by a process of conceptual blending using image schemas.
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References
Clementini, E., Felice, P.D., Hernandez, D.: Qualitative representation of positional information. Artif. Intell. 95(2), 317–356 (1997)
Cohn, A.G., Renz, J.: Qualitative spatial reasoning, handbook of knowledge representation. Elsevier, Wiley-ISTE, London (2007)
Confalonieri, R., Corneli, J., Pease, A., Plaza, E., Schorlemmer, M.: Using argumentation to evaluate concept blends in combinatorial creativity. In: Toivonen, H., Colton, S., Cook, M., Ventura, D. (eds.) Proceedings of the 6th international conference on computational creativity, pp. 174–181, Park City (2015)
Confalonieri, R., Pease, A., Schorlemmer, M., Besold, T., Kutz, O., Maclean, E., Kaliakatsos-Papakostas, M. (eds.): Concept invention: Foundations, implementation, social aspects and applications. Springer, Berlin (2018)
Confalonieri, R., Eppe, M., Schorlemmer, M., Kutz, O., Pe naloza, R., Plaza, E.: Upward refinement operators for conceptual blending in the description logic EL++. Annals of Mathematics and Artificial Intelligence, 1–31. https://doi.org/10.1007/s10472-016-9524-8 (2016)
Confalonieri, R., Plaza, E., Schorlemmer, M.: A process model for concept invention. In: Pachet, F., Cardoso, A., Corruble, V., Ghedini, F. (eds.) Proceedings of the 7th international conference on computational creativity, pp. 338–345, Paris (2016)
Cui, Z., Cohn, A.G., Randell, D.A.: Qualitative and topological relationships in spatial databases. In: Abel, D.J., Ooi, B.C. (eds.) Advances in spatial databases, 3rd international symposium, SSD’93, June 23-25, 1993 Proceedings, volume 692 of lecture notes in computer science, pp. 296–315. Springer, Singapore (1993)
Cunha, J.M., Gonċalves, J., Martins, P., Machado, P., Cardoso, A.: A pig, an angel and a cactus walk into a blender: A descriptive approach to visual blending. arXiv:1706.09076 (2017)
Davis, E., Marcus, G., Chen, A.: Reasoning from radically incomplete information: The case of containers. Advances in Cognitive Systems 2, 1–18 (2013)
Egenhofer, M., Herring, J.: Categorizing binary topological relationships between regions, lines, and points in geographic databases. Department of Surveying Engineering, University of Maine, Orono ME (1991)
Egenhofer, M.A.X.J., Franzosa, R.: Point-set topological spatial relations. Int. J. Geogr. Inf. Syst. 5(2), 161–174 (1991)
Eppe, M., Maclean, E., Confalonieri, R., Kutz, O., Schorlemmer, M., Plaza, E., Kühnberger, K.-U.: A computational framework for conceptual blending. Artif. Intell. 256, 105–129 (2018)
Falomir, Z.: Towards a qualitative descriptor for paper folding reasoning. In: Proc. of the 29th International Workshop on Qualitative Reasoning, 2016. Co-located with IJCAI’2016 in New York, USA
Falomir, Z., Gonzalez-Abril, L., Museros, L., Ortega, J.: Measures of similarity between objects from a qualitative shape description. Spat. Cogn. Comput. 13, 181–218 (2013). https://doi.org/10.1080/13875868.2012.700463
Falomir, Z., Museros, L., Castelló, V., Gonzalez-Abril, L.: Qualitative distances and qualitative image descriptions for representing indoor scenes in robotics. Pattern Recogn. Lett. 38, 731–743 (2013). https://doi.org/10.1016/j.patrec.2012.08.012
Falomir, Z., Olteţeanu, A.-M.: Logics based on qualitative descriptors for scene understanding. Neurocomputing 161, 3–16 (2015). https://doi.org/10.1016/j.neucom.2015.01.074
Falomir, Z., Pich, A., Costa, V.: Spatial reasoning about qualitative shape compositions: Composing qualitative lengths and angles. Annals of mathematics and artificial intelligence, page submitted (2018)
Falomir, Z.: A qualitative model for reasoning about 3d objects using depth and different perspectives. In: Lechowski, T., Wałȩga, P., Zawidzki, M. (eds.) LQMR 2015 Workshop, volume 7 of annals of computer science and information systems, pp. 3–11, PTI. https://doi.org/10.15439/2015F370. (2015)
Falomir, Z., Rahman, S.: From qualitative descriptors of movement towards spatial logics for videos. In: Azzopardi, G et al. (eds.) Proc. 3rd Workshop on Recognition and Action for Scene Understanding (REACTS), co-located at 16th Int. Conf. Computer Analysis of Images and Patterns (CAIP), ISBN 978-84-606-9592-9, pp. 119–128 (2015)
Fauconnier, G., Turner, M.: The way we think: Conceptual blending and the mind’s hidden complexities. Basic Books, New York (2003)
Forbus, K.D.: Qualitative modeling. Wiley Interdisciplinary Reviews. Cognit. Sci. 2(4), 374–391 (2011)
Frank, A.U.: Qualitative spatial reasoning with cardinal directions. In: Kaindl, H. (ed.) 7. Österreichische artificial intelligence tagung. Springer, Berlin (1991)
Goguen, J.: An introduction to algebraic semiotics, with applications to user interface design. In: Nehaniv, C.L. (ed.) Computation for metaphors, analogy, and agents, volume 1562 of lecture notes in computer science, pp. 242–291. Springer (1999)
Gonċalves, J., Martins, P., Cardoso, A.: Blend city, blendville. In: Goel, A., Jordanous, A., Peas, A. (eds.) Proceedings of the Eighth International Conference on Computational Creativity, pp. 112–119 (2017)
Grice, P.: Meaning. Philos. Rev. 66, 377–88 (1957). Reprinted in [26] pages 213–223
Grice, P.: Studies in the way of words. Harvard University Press, Harvard (1989)
Hedblom, M.M., Kutz, O., Neuhaus, F.: Choosing the right path Image schema theory as a foundation for concept invention. J. Artificial General Intelligence 6(1), 21–54 (2015)
Hernández, D.: Relative representation of spatial knowledge: The 2-D case. In: Mark, D.M., Frank, A.U. (eds.) Cognitive and linguistic aspects of geographic Space, pp. 373–385. NATO Advanced Studies Institute, Kluwer (1991)
Johnson, M.: The body in the mind: The bodily basis of meaning, imagination, and reason. University Of Chicago Press, Chicago (1987)
Johnson, M.: The philosophical significance of image schemas. In: Hampe, B., Grady, J.E. (eds.) From perception to meaning: Image schemas in cognitive linguistics. ISBN-13: 978-3-11-018311-5, pp. 15–33. Mouton de Gruyter, Berlin & New York (2005)
Kurata, Y., Egenhofer, M.J.: The arrow-semantics interpreter. Spatial Cognition & Computation: An Interdisciplinary Journal 8(4), 306–332 (2008)
Lakoff, G., Núñez, R.E.: Where mathematics comes from: How the embodied mind brings mathematics into being basic books (2000)
Lakoff, G.: Women, fire and dangerous things: What categories reveal about the mind. University of Chicago Press, Chicago (1987)
Ligozat, G.: Qualitative spatial and temporal reasoning. MIT Press, Wiley-ISTE, London (2011)
Lovett, A., Forbus, K.: Modeling visual problem solving as analogical reasoning. Psychol. Rev. 124(1), 60–90 (2017)
Moratz, R., Dylla, F., Frommberger, L.: A relative orientation algebra with adjustable granularity. In: Proceedings of the workshop on agents in real-time and dynamic environments (IJCAI 05) (2005)
Olteteanu, A.-M., Falomir, Z.: Object replacement and object composition in a creative cognitive system. A computational counterpart of the alternative use test. Cogn. Syst. Res. 39, 15–32 (2016)
Ontañón, S., Plaza, E.: Amalgams: A formal approach for combining multiple case solutions. In: ICCBR’10: 18th international conference on case-based reasoning, volume 6176 of lecture notes in artificial intelligence, pp. 257–271. Springer (2010)
Pereira, F.C., Cardoso, A.: Experiments with free concept generation in divago. Knowl.-Based Syst. 19(7), 459–470 (2006)
Pich, A., Falomir, Z.: Logical composition of qualitative shapes applied to solve spatial reasoning tests. Cogn. Syst. Res. 52, 82–102 (2018)
Stock, O: Spatial and temporal reasoning. Kluwer Academic Publishers, Norwell (1997)
Acknowledgments
This research has been partially supported by Cognitive Qualitative Descriptions and Applications (CogQDA) of the Central Research Development Fund (CRDF) at University of Bremen through the 04-Independent Projects for Postdocs action and project DIVERSIS (CSIC Intramural 201750E064).
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Falomir, Z., Plaza, E. Towards a model of creative understanding: deconstructing and recreating conceptual blends using image schemas and qualitative spatial descriptors. Ann Math Artif Intell 88, 457–477 (2020). https://doi.org/10.1007/s10472-019-09619-9
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DOI: https://doi.org/10.1007/s10472-019-09619-9
Keywords
- Computational creativity
- Concept blending
- Qualitative spatial descriptors
- Image schemas
- Concept understanding
- Novel concepts