Computational Approaches to Storytelling and Creativity (original) (raw)

Book Reviews: The creative process: A computer model of storytelling and creativity

1995

Within cognitive science and psychology, there has been a good deal of interest recently in the topic of creativity. In this book, Scott Turner of the University of California, Los Angeles, presents a theory of creativity applied to generating small stories. Turner can be thought of as a member of the third generation of the Schank family: first, of course, there was grandfather Roger Schank, who in the 1970s with Robert Abelson at Yale, embarked on the research project of understanding narrative text using the ideas of goals, plans, and scripts. The attempt was to propose computational models that would accomplish aspects of narrative understanding. The second generation was a talented group of people, including Wendy Lehnert and Robert Wilensky, who did their Ph.D.s at Yale on story understanding. Turner is a member of a third generation, advised by Michael Dyer who also obtained his Ph.D. at Yale and then moved to an academic position at UCLA. Dyer had turned his attention to sto...

Towards Machines for Measuring Creativity: The Use of Computational Tools in Storytelling Activities

2014 IEEE 14th International Conference on Advanced Learning Technologies, 2014

Until now, significant R&D effort in the field of Computational Creativity, has been devoted towards understudying the elements of the creative process from idea conception to production, or towards designing machines which exhibit human level creativity without merely mimicking the human creative process. However, in the effort to determine if an artefact is creative by human standards, it is also important to examine the perception of creativity by humans and to which extend this perception can be formalized and applied on the evaluation of creative works. In this paper, we investigate how the human perception for creativity exhibited in text artefacts can be predicted using appropriate formulations of computational creativity metrics. To this end, we designed and executed a storytelling experiment assisted by the usage of computational tools. We subsequently exploited humanprovided rankings of the stories in order to train a model for evaluating creativity as a combination of various characteristics of the produced stories.

Leaps and Bounds: An Introduction to the Field of Computational Creativity

New Generation Computing

Computers have enhanced productivity and cost-effectiveness in all of the creative industries, and their value as tools is rarely doubted. But can machines serve as more than mere tools, and assume the role and responsibilities of a co-creative partner, or even become goal-setting, autonomous creators in their own right? These are the questions that define the discipline of computational creativity. The answers require an algorithmic understanding of how humans give meaning to form, but a transformation in the way we think about creativity is unlikely to occur in a single bound. Rather, interdisciplinary insights from diverse fields must first inform our models, and shape a narrative of creativity in which machines are both tools and creators. To set the stage for the newest work, this introduction to the special issue on computational creativity shows where the field is going, and where it has come from.

[PDF]Whence is Creativity? - Computational Creativity

2012

We start with a critical examination of the traditional view of creativity in which the creator is the major player. We analyze many different examples to point out that the origin of all different creativity scenarios is rooted in the viewer-artifact interaction. To recognize this explicitly, we propose an alternative formulation of creativity by putting the viewer in the driver's seat. We examine some implications of this formulation, especially for the role of computers in creativity, and argue that it captures the essence of creativity more accurately.

Experiments with computational creativity

Neural Information Processing–Letters …, 2007

Neurocognitive model inspired by the putative processes in the brain has been applied to invention of novel words. This domain is proposed as the simplest way to understand creativity using experimental and computational means. Three factors are essential for creativity in this domain: knowledge of the statistical language properties, imagination constrained by this knowledge, and filtering of results that selects most interesting novel words. These principles are implemented using a simple correlation-based algorithm for auto-associative memory that learns the statistical properties of language. Results are surprisingly similar to those created by humans. Perspectives on computational models of creativity are discussed.

Can a Computationally Creative System Create Itself? Creative Artefacts and Creative Processes

This paper begins by briefly looking at two of the dominant perspectives on computational creativity; focusing on the creative artefacts and the creative processes respectively. We briefly describe two projects; one focused on (artistic) creative artefacts the other on a (scientific) creative process, to highlight some similarities and differences in approach. We then look at a 2-dimensional model of Learning Objectives that uses independent axes of knowledge and (cognitive) processes. This educational framework is then used to cast artefact and process perspectives into a common framework, opening up new possibilities for discussing and comparing creativity between them. Finally, arising from our model of creative processes, we propose a new and broad 4-level hierarchy of computational creativity, which asserts that the highest level of computational creativity involves processes whose creativity is comparable to that of the originating process itself.