How Did Humans Become So Creative? A Computational Approach

Aus de_evolutionary_art_org
Wechseln zu: Navigation, Suche

Reference

Gabora, L., Steve DiPaola: How Did Humans Become So Creative? A Computational Approach. In: Computational Creativity 2012 ICCC 2012, 203-210.

DOI

Abstract

This paper summarizes efforts to computationally mod- el two transitions in the evolution of human creativity: its origins about two million years ago, and the ̳big bang‘ of creativity about 50,000 years ago. Using a computational model of cultural evolution in which neural network based agents evolve ideas for actions through invention and imitation, we tested the hypothe- sis that human creativity began with onset of the capaci- ty for recursive recall. We compared runs in which agents were limited to single-step actions to runs in which they used recursive recall to chain simple actions into complex ones. Chaining resulted in higher diversi- ty, open-ended novelty, no ceiling on the mean fitness of actions, and greater ability to make use of learning. Using a computational model of portrait painting, we tested the hypothesis that the explosion of creativity in the Middle/Upper Paleolithic was due to onset of con- textual focus: the capacity to shift between associative and analytic thought. This resulted in faster conver- gence on portraits that resembled the sitter, employed painterly techniques, and were rated as preferable. We conclude that recursive recall and contextual focus pro- vide a computationally plausible explanation of how humans evolved the means to transform this planet.

Extended Abstract

Bibtex

@inproceedings{
author = {Liane Gabora, Steve DiPaola},
title = {How Did Humans Become So Creative? A Computational Approach},
editor = {Mary Lou Maher, Kristian Hammond, Alison Pease, Rafael Pérez y Pérez, Dan Ventura and Geraint Wiggins},
booktitle = {Proceedings of the Third International Conference on Computational Creativity},
series = {ICCC2012},
year = {2012},
month = {May},
location = {Dublin, Ireland},
pages = {203-210},
url = {http://computationalcreativity.net/iccc2012/wp-content/uploads/2012/05/203-Gabora.pdf, http://de.evo-art.org/index.php?title=How_Did_Humans_Become_So_Creative%3F_A_Computational_Approach },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}

Used References

Barkow, J. H., Cosmides, L., & Tooby, J., Eds. 1992. The Adapted Mind: Evolutionary Psychology and the Genera- tion of Culture. New York: Oxford University Press.

Bentley, P., D. Corne D., Eds. 2002. Creative Evolutionary Systems, Morgan Kaufmann, San Francisco.

Bentley, R. A., Ormerod, P., & Batty, M. 2011. Evolving social influence in large populations. Behavioral Ecology and Sociobiology, 65:537–546.

Boden, M. 2003. The Creative Mind: Myths and Mecha- nisms (second edition). Routledge.

Brown, J. 2009. Looking at Darwin: portraits and the mak- ing of an icon. Isis. Sept, 100(3):542–70.

Buller, D. J. 2005. Adapting minds. MIT Press.

Buss, D. M. 19992004. Evolutionary Psychology: The new science of the mind. Boston, MA: Pearson.

Byrne, R., & Russon, A. 1998. Learning by imitation: A hierarchical approach. Behav Brain Sciences, 2:667–721.

Cavalli-Sforza, L. L., & Feldman, M. W. 1981. Cultural Transmission and Evolution: A Quantitative Approach. Princeton: Princeton University Press.

Cloak, F. T. Jr. 1975. Is a cultural ethology possible? Hu- man Ecology, 3:161–182.

DiPaola, S. & Gabora, L. 2007. Incorporating characteris- tics of human creativity into an evolutionary art algorithm. In (D. Thierens, Ed.), Proc Genetic and Evol Computing Conf (pp. 2442–2449), July 7-11, Univ College London.

DiPaola S, 2009. ―Exploring a Parameterized Portrait Painting Space”, International Journal of Art and Tech- nology, 2(1-2):82–93.

DiPaola, S. & Gabora, L. 2009. Incorporating characteris- tics of human creativity into an evolutionary art algorithm. Genet Prog and Evolvable Machines, 10(2):97–110.

Donald, M. 1991. Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition. Cam- bridge, MA: Harvard University Press.

Dugatkin, L. 2001. A. Imitation Factor: Imitation in Ani- mals and the Origin of Human Culture. Free Press.

Gabora, L. 1995. Meme and Variations: A computer model of cultural evolution. In L. Nadel & D. Stein (Eds.) 1993 Lectures in Complex Systems. Addison-Wesley, 471−486.

Gabora, L. 1996. A day in the life of a meme. Philosophi- ca, 57:901–938.

Gabora, L. 1999. Conceptual closure: Weaving memories into an interconnected worldview. In (G. Van de Vijver & J. Chandler, Eds.) Proc Closure: Intl Conf Emergent Or- ganizations and Dynamics. May 3-5, Univ Gent, Belgium.

Gabora, L. 2008a. EVOC: A computer model of cultural evolution. In V. Sloutsky, B. Love & K. McRae (Eds.), Proc Ann Mtng Cog Sci Soc, Sheridan Publ, 1466–1471.

Gabora, L. Modeling cultural dynamics. 2008b. In Pro- ceedings of the Association for the Advancement of Artifi- cial Intelligence (AAAI) Fall Symposium 1: Adaptive Agents in a Cultural Context, AAAI Press, 18–25.

Gabora, L. & Aerts, D. 2009. A mathematical model of the emergence of an integrated worldview. Journal of Mathe- matical Psychology, 53:434-451.

Gabora, L. & Leijnen, S. 2009. How creative should crea- tors be to optimize the evolution of ideas? A computational model. Electronic Proc Theor Comp Sci, 9:108–119.

Gabora, L. & Saberi, M. 2011. How did human creativity arise? An agent-based model of the origin of cumulative open-ended cultural evolution. Proceedings:ACM Confer- ence on Cognition & Creativity, 299-306. Atlanta, GA.

Hartley, J. 2009. From cultural studies to cultural science. Cultural Science, 2:1–16.

Higgs, P. 2000. The mimetic transition: a simulation study of the evolution of learning by imitation. Proceedings: Royal Society B: Biological Sciences, 267:1355–1361.

Heyes, C. M. 1998. Theory of mind in nonhuman primates. Behavioral and Brain Sciences, 211:104–134.

Hinton, G. E. & Nowlan, S. J. 1987. How learning can guide evolution. Complex Systems, 1:495–502.

Holland, J. K. 1975. Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press.

Hutchins, E. & Hazelhurst, B. 1991. Learning in the cul- tural process. In Langton, C., Taylor, J., Farmer, D., &Rasmussen, S. (Eds.) Artificial Life II. Redwood City, CA: Addison-Wesley.

Jennings, K. E. 2010. Developing creativity: Artificial bar- riers in artificial intelligence. Minds and Machines, 1–13.

Kirby, S. 2001. Spontaneous evolution of linguistic Struc- ture—An iterated learning model of the emergence of regularity and irregularity. IEEE Transactions on Evolu- tionary Computation, 5(2):102–110.

Koza, J, 1993. Genetic Programming, MIT Press.

Leijnen, S. & Gabora, L. 2010. An agent-based simulation of the effectiveness of creative leadership. Proc Ann Mtng Cog Sci Soc 955–960. Aug 11-14, Portland, OR.

Mesoudi, A., Whiten, A., & Laland, K. 2006. Toward a unified science of cultural evolution. Behavioral and Brain Sciences, 29:329–383.

Miller, J. 2011. Cartesian Genetic Programming, Springer.

Mithen, S. Ed. 1998. Creativity in Human Evolution and Prehistory. London, UK: Routledge.

Padian, K. 2008. Darwin's Enduring Legacy, Nature, 451:632–634.

Pease, A. and Colton, S. 2011. On Impact and Evaluation in Computational Creativity: A Discussion of the Turing Test and an Alternative Proposal. In Proceedings of the AISB symposium on AI and Philosophy.

Ritchie, G. 2007. Some empirical criteria for attributing creativity to a computer program. Minds and Machines 17.

Colton, S., Pease, A, Charnley. J. 2011 Computational cre- ativity theory: The FACE and IDEA descriptive models. In 2nd Int Conference on Computational Creativity.

Ruff, C., Trinkaus, E., & Holliday, T. 1997. Body mass and encephalization in Pleistocene Homo. Nature, 387:173–176.

Tomasello, M., Kruger, A., Ratner, H. 1993. Cultural learning. Behavioral and Brain Sciences, 16:495–552.

Wexler, B. 2006. Brain and Culture: Neurobiology, Ideol- ogy and Social Change. New York: Bradford Books.

Whiten, A., Hinde, R., Laland, K., Stringer, C. 2011. Cul- ture evolves. 2011. Philosophical Transactions of the Roy- al Society B, 366:938–948.

Wiggins, G. 2006. A preliminary framework for descrip- tion, analysis and comparison of creative systems. Knowledge-Based Systems 19(7):449-458.


Links

Full Text

http://computationalcreativity.net/iccc2012/wp-content/uploads/2012/05/203-Gabora.pdf

http://ivizlab.sfu.ca/papers/iccc2012.pdf

intern file

Sonstige Links

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.388.5479