AGI 2012: Artificial General Intelligence pp 1-10 | Cite as
Creativity, Cognitive Mechanisms, and Logic
Abstract
Creativity is usually not considered to be a major issue in current AI and AGI research. In this paper, we consider creativity as an important means to distinguish human-level intelligence from other forms of intelligence (be it natural or artificial). We claim that creativity can be reduced in many interesting cases to cognitive mechanisms like analogy-making and concept blending. These mechanisms can best be modeled using (non-classical) logical approaches. The paper argues for the usage of logical approaches for the modeling of manifestations of creativity in order to step further towards the goal of building an artificial general intelligence.
Keywords
Logic Creativity Analogy Concept Blending Cognitive MechanismsPreview
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References
- 1.Abdel-Fattah, A., Besold, T.R., Gust, H., Krumnack, U., Schmidt, M., Kühnberger, K.-U., Wang, P.: Rationality-Guided AGI as Cognitive Systems. In: Proc. of the 34th Annual Meeting of the Cognitive Science Society (2012)Google Scholar
- 2.Alexander, J.: Blending in Mathematics. Semiotica 2011(187), 1–48 (2011)CrossRefGoogle Scholar
- 3.Argand, J.-R.: Philosophie mathématique. Essay sur une manière de représenter les quantités imaginaires, dans les constructions géométriques. Annales de Mathématiques Pures et Appliquées 4, 133–146 (1813)Google Scholar
- 4.Boden, M.: The Creative Mind: Myths and Mechanisms. Taylor & Francis (2003)Google Scholar
- 5.Burki, L., Cavallucci, D.: Measuring the Results of Creative Acts in R&D: Literature Review and Perspectives. In: Cavallucci, D., De Guio, R., Cascini, G. (eds.) CAI 2011. IFIP AICT, vol. 355, pp. 163–177. Springer, Heidelberg (2011)CrossRefGoogle Scholar
- 6.Chomsky, N.: Syntactic structure. Mouton, The Hague (1957)Google Scholar
- 7.Colton, S.: The painting fool in new dimensions. In: Show, Tell (eds.) Proceedings of the 2nd International Conference on Computational Creativity (2011)Google Scholar
- 8.Fauconnier, G., Turner, M.: The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. Basic Books, New York (2002)Google Scholar
- 9.Goguen, J.: Mathematical models of cognitive space and time. In: Andler, D., Ogawa, Y., Okada, M., Watanabe, S. (eds.) Reasoning and Cognition: Proc. of the Interdisciplinary Conference on Reasoning and Cognition, pp. 125–128. Keio University Press (2006)Google Scholar
- 10.Guhe, M., Pease, A., Smaill, A., Martínez, M., Schmidt, M., Gust, H., Kühnberger, K.-U., Krumnack, U.: A computational account of conceptual blending in basic mathematics. Cognitive Systems Research 12(3-4), 249–265 (2011)CrossRefGoogle Scholar
- 11.Hofstadter, D.R.: The Copycat Project: An Experiment in Non Determinism and Creative Analogies. A.I. Mema. Massachusetts Institute of Technology, Artificial Intelligence Laboratory (1984)Google Scholar
- 12.Hummel, J.E., Holyoak, K.J.: A symbolic-connectionist theory of relational inference and generalization. Psychological Review 110, 220–264 (2003)CrossRefGoogle Scholar
- 13.Kokinov, B., Petrov, A.: Integration of memory and reasoning in analogy-making: The ambr model. In: Gentner, D., Holyoak, K., Kokinov, B. (eds.) The Analogical Mind: Perspectives from Cognitive Science. MIT Press, Cambridge (2001)Google Scholar
- 14.Krumnack, U., Schwering, A., Gust, H., Kühnberger, K.-U.: Restricted Higher-Order Anti-Unification for Analogy Making. In: Orgun, M.A., Thornton, J. (eds.) AI 2007. LNCS (LNAI), vol. 4830, pp. 273–282. Springer, Heidelberg (2007)CrossRefGoogle Scholar
- 15.Lakoff, G., Núñez, R.: Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being. Basic Books, New York (2000)MATHGoogle Scholar
- 16.Martinez, M., Besold, T.R., Abdel-Fattah, A., Kühnberger, K.-U., Gust, H., Schmidt, M., Krumnack, U.: Towards a domain-independent computational framework for theory blending. In: AAAI Technical Report of the AAAI Fall 2011 Symposium on Advances in Cognitive Systems, pp. 210–217 (2011)Google Scholar
- 17.Newell, A., Shaw, J., Simon, H.: The process of creative thinking. In: Gruber, H., Terrell, G., Wertheimer, M. (eds.) Contemporary Approaches to Creative Thinking, Atherton, New York, pp. 63–119 (1963)Google Scholar
- 18.Pereira, F.C., Cardoso, A.: Optimality principles for conceptual blending: A first computational approach. AISB Journal 1 (2003)Google Scholar
- 19.Pereira, F.C.: Creativity and AI: A Conceptual Blending Approach. Applications of Cognitive Linguistics (ACL). Mouton de Gruyter, Berlin (2007)Google Scholar
- 20.Schwering, A., Krumnack, U., Kühnberger, K.-U., Gust, H.: Syntactic principles of heuristic-driven theory projection. Cognitive Systems Research 10(3), 251–269 (2009)CrossRefGoogle Scholar
- 21.Schwering, A., Kühnberger, K.-U., Krumnack, U., Gust, H., Wandmacher, T.: A computational model for visual metaphors. Interpreting creative visual advertisements. In: Indurkhya, B., Ojha, A. (eds.) Proceedings of International Conference on Agents and Artificial Intelligence, ICAART 2009 (2009)Google Scholar
- 22.Veale, T., O’Donoghue, D.: Computation and Blending. Computational Linguistics 11(3-4), 253–282 (2000); Special Issue on Conceptual BlendingGoogle Scholar
- 23.Wallas, G.: The art of thought. C.A. Watts & Co. Ltd., London (1926)Google Scholar