Conceptual blending

In Cognitive Linguistics, Conceptual blending, also called conceptual integration or view application, is a theory of cognition developed by Gilles Fauconnier and Mark Turner. According to this theory, elements and vital relations from diverse scenarios are "blended" in a subconscious process, which is assumed to be ubiquitous to everyday thought and language. Much like memetics, it is an attempt to create a unitary account of the cultural transmission of ideas.[1]

History

The development of this theory began in 1993 and a representative early formulation is found in the online article Conceptual Integration and Formal Expression.[2] Turner and Fauconnier cite Arthur Koestler's 1964 book The Act of Creation as an early forerunner of conceptual blending: Koestler had identified a common pattern in creative achievements in the arts, sciences and humor that he had termed "bisociation of matrices."[3] A newer version of blending theory, with somewhat different terminology, was presented in Turner and Fauconnier's 2002 book, The Way We Think.[4] Conceptual blending, in the Fauconnier and Turner formulation, is one of the theoretical tools used in George Lakoff and Rafael Núñez's Where Mathematics Comes From, in which the authors assert that "understanding mathematics requires the mastering of extensive networks of metaphorical blends."[5]

Computational models

Conceptual blending is closely related to frame-based theories, but goes beyond these primarily in that it is a theory of how to combine frames (or frame-like objects). An early computational model of a process called "view application", which is closely related to conceptual blending (which did not exist at the time), was implemented in the 1980s by Shrager at Carnegie Mellon University and PARC, and applied in the domains of causal reasoning about complex devices[6] and scientific reasoning.[7] More recent computational accounts of blending have been developed in areas such as mathematics.[8] Some later models are based upon Structure Mapping, which did not exist at the time of the earlier implementations. Recently, within the context of non-monotonic extensions of AI reasoning systems (and in line with the frame-based theories), a general framework able to account for both complex human-like concept combinations (like the PET-FISH problem) and conceptual blending [9] has been tested and developed in both cognitive modelling [10] and computational creativity applications [11] [12].

The philosophical status of the theory

In his book The Literary Mind[13] (p. 93), conceptual blending theorist Mark Turner states that

Conceptual blending is a fundamental instrument of the everyday mind, used in our basic construal of all our realities, from the social to the scientific.

Insights obtained from conceptual blends constitute the products of creative thinking, however conceptual blending theory is not itself a complete theory of creativity, inasmuch as it does not illuminate the issue of where the inputs to a blend originate. In other words, conceptual blending provides a terminology for describing creative products, but has little to say on the matter of inspiration.

See also

Notes
  1. Ritchie, L. David (2004). "Lost in "conceptual space": Metaphors of conceptual integration". Metaphor and Symbol. 19: 31–50. Retrieved 2020-06-14.
  2. Conceptual Integration and Formal Expression Archived 2006-05-16 at the Wayback Machine
  3. Mark Turner, Gilles Fauconnier: The Way We Think. Conceptual Blending and the Mind's Hidden Complexities. New York: Basic Books 2002, p. 37
  4. Fauconnier, Gilles; Turner, Mark (2008), The Way We Think: Conceptual Blending and the Mind's Hidden Complexities, Basic Books.
  5. Lakoff, George; Núñez, Rafael (2003), Where mathematics comes from, Basic Books, p. 48, ISBN 0-465-03770-4
  6. Shrager, J. (1987) Theory Change via View Application in Instructionless Learning. Machine Learning 2 (3), 247–276.
  7. Shrager, J. (1990) Commonsense perception and the psychology of theory formation. In Shrager & Langley (Eds.) Computational models of scientific discovery and theory formation. San Mateo, CA: Morgan Kaufmann.
  8. Guhe, Markus, Alison Pease, Alan Smaill, Maricarmen Martinez, Martin Schmidtb, Helmar Gust, Kai-Uwe Kühnberger and Ulf Krumnack (2011). A computational account of conceptual blending in basic mathematics. Cognitive Systems Research Volume 12, Issues 3–4, September–December 2011, pp. 249–265 Special Issue on Complex Cognition
  9. Lieto, A.; Pozzato, G.L. (2020). "A description logic framework for commonsense conceptual combination integrating typicality, probabilities and cognitive heuristics". Journal of Experimental and Theoretical Artificial Intelligence. arXiv:1811.02366. doi:10.1080/0952813X.2019.1672799.
  10. Lieto, A.; Perrone, F.; Pozzato, G.L.; Chiodino, E. (2019). "Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architectures". Cognitive Systems Research. doi:10.1016/j.cogsys.2019.08.005. hdl:2318/1726157.
  11. Lieto, A.; Pozzato, G.L. (2019). "Applying a description logic of typicality as a generative tool for concept combination in computational creativity". Intelligenza Artificiale. doi:10.3233/IA-180016.
  12. Chiodino, E.; Di Luccio, D.; Lieto, A.; Messina, A.; Rubinetti, D.; Pozzato, G.L. (2020). "A Knowledge-based System for the Dynamic Generation and Classification of Novel Contents in Multimedia Broadcasting, Proceedings of ECAI 2020, 24th European Conference on Artificial Intelligence, 2020". Cite journal requires |journal= (help)
  13. Turner, Mark (1997), The literary mind, Oxford University Press.
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