%0 Book Section %B Artificial Intelligence and the Arts: Computational Creativity, Artistic Behavior, and Tools for Creatives %D 2021 %T Computational Models of Narrative Creativity %A Pablo Gervás %E Machado, Penousal %E Romero, Juan %E Greenfield, Gary %X Ever since the advent of computers there have been research efforts to emulate computationally the way in which people can create stories. Artificial intelligence (AI) and the myriad of specific technologies it brought with it gave rise to more elaborate efforts. Yet the task seems to be a challenging frontier that even today still defeats efforts to achieve performance comparable to that of humans. In part, the difficulty lies in the fact that the approaches computers have been following to date differ significantly from those applied by humans on a number of points. Whereas computers generally apply a single specific AI technique to these problems, humans seem to combine several cognitive abilities into the task. Computers focus on the short end of narrative production (fairy tales and short stories) but humans produce in a much wider range, with long examples of much greater complexity (novels, plays, films) being very frequent. Where computers usually apply a one-pass algorithm that produces a single output or focus on generating small fragments of an interactive piece in co-operation with a human, the basic mode of operation for human authors is to work alone and to proceed by iteratively revising a draft based on critical appraisal of whether it meets very demanding criteria. The present chapter reviews the existing approaches to computational generation of (emulations of) narrative under the light of these differences in procedure. To inform this review, some of the existing models of how humans address the corresponding tasks are described and the existing computational solutions are examined for similarities and differences with these models of human performance. The impact of these various aspects on the quality of computer generated artifacts is considered and an analysis of current trends for future development is made, with particular emphasis on how addressing the aspects that have so far been less studied may help change the landscape of the field. %B Artificial Intelligence and the Arts: Computational Creativity, Artistic Behavior, and Tools for Creatives %I Springer International Publishing %C Cham %P 209–255 %@ 978-3-030-59475-6 %G eng %U https://doi.org/10.1007/978-3-030-59475-6_9 %& 9 %R 10.1007/978-3-030-59475-6_9 %0 Journal Article %J ACM Comput. Surv. %D 2019 %T Conceptual Representations for Computational Concept Creation %A Xiao, Ping %A Hannu Toivonen %A Gross, Oskar %A Cardoso, Amílcar %A Correia, João %A Machado, Penousal %A Martins, Pedro %A Hugo Gonçalo Oliveira %A Sharma, Rahul %A Pinto, Alexandre Miguel %A Díaz, Alberto %A Virginia Francisco %A Pablo Gervás %A Hervás, Raquel %A Carlos León %A Forth, Jamie %A Purver, Matthew %A Wiggins, Geraint A. %A Miljković, Dragana %A Podpečan, Vid %A Pollak, Senja %A Kralj, Jan %A Żnidaršič, Martin %A Bohanec, Marko %A Nada Lavrac %A Urbančič, Tanja %A Velde, Frank Van Der %A Battersby, Stuart %B ACM Comput. Surv. %V 52 %P 9:1–9:33 %G eng %U http://doi.acm.org/10.1145/3186729 %R 10.1145/3186729 %> http://nil.fdi.ucm.es/sites/default/files/a9-xiao-with-supp.pdf