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enaction provides a helpful way to reframe creativity and potentially solve some of
the long-standing hard problems that both artifi cial intelligence and computational
creativity face. The theory of enaction was used to describe creativity in design,
music, and visual art to show its potential for generalizability and descriptive power.
We also presented the enactive model of creativity that formalized the enaction
theory in a computational model. Finally, we describe how the enactive model of
creativity was helpful in designing two computer colleagues, one in the domain of
visual art and the other in the domain of design. The primary design principle of the
enactive model of creativity is to design interactions like a conversation where each
party tries to make sense of contributions and respond appropriately given the his-
tory of interaction.
References
Adamson RE (1952) Functional fi xedness as related to problem solving: a repetition of three
experiments. J Exp Psychol 44(4):288-291
Arnheim R (1954) Art and visual perception. University of California Press, Oakland
Barsalou LW (1999) Perceptual symbol systems. Behav Brain Sci 22(04):637-660
Biles JA (2003) GenJam in perspective: a tentative taxonomy for GA music and art systems.
Leonardo 36(1):43-45
Boden MA (2004) The creative mind: myths and mechanisms. Psychology Press, New York
Bono ED (1970) Lateral thinking: a textbook of creativity. Ward Lock Educational/El pensamiento
lateral: manual de creatividad, Londres/Versión española
Candy L (1997) Computers and creativity support: knowledge, visualisation and collaboration.
Knowl-Based Syst 10(1):3-13
Carroll EA, Latulipe C, Fung R, Terry M (2009) Creativity factor evaluation: towards a standard-
ized survey metric for creativity support. In: Proceedings of the seventh ACM conference on
creativity and cognition. ACM, New York, pp 127-136
Colton S, Wiggins GA (2012) Computational creativity: the fi nal frontier? In: Proceedings of
European conference on artifi cial intelligence, pp 21-26
Colton S, Goodwin J, Veale T (2012) Full face poetry generation. In: Proceedings of the third
international conference on computational creativity. International Conference on
Computational Creativity, pp 95-102
Csikszentmihalyi M (1997) Flow and the psychology of discovery and invention. HarperPerennial,
New York
Davis N, Li B, O'Neill B, Riedl M, Nitsche M (2011) Distributed creative cognition in digital fi lm-
making. In: Proceedings of the 8th ACM conference on creativity and cognition. ACM,
New York, pp 207-216
Davis N, Popova Y, Sysoev I, Hsiao CP, Zhang D, Magerko B (2014) Building artistic computer
colleagues with an enactive model of creativity. In: Proceedings of the fi fth international con-
ference on computational creativity. The International Association for Computational
Creativity, pp 38-45
De Jaegher H (2009) Social understanding through direct perception? Yes, by interacting.
Conscious Cogn 18(2):535-542
Dixon D, Prasad M, Hammond T (2010) iCanDraw: using sketch recognition and corrective feed-
back to assist a user in drawing human faces. In: Proceedings of the SIGCHI conference on
human factors in computing systems. ACM, New York, pp 897-906
Engel AK (2010) Directive minds: how dynamics shapes cognition. In: Enaction: towards a new
paradigm for cognitive science. MIT Press, Cambridge, MA, pp 219-243
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