Bridging the Gap Between AI, Cognitive Science, and Narratology With Narrative Generation

2021 ◽  
2018 ◽  
pp. 156-229 ◽  
Author(s):  
Takashi Ogata

This chapter surveys and discusses interdisciplinary approaches to primarily Artificial Intelligence (AI)-based computational narrative or story generation systems by way of introducing cognitive science, and narratology and related literary theories. The first part of this chapter provides a general description (from the perspective of the research framework of the author) and the second part presents processes, theories, designs, and implementations of narrative generation by the author. In particular, the first part includes an overview of narratology and the relevant literary theories, computational and cognitive theories and techniques related to narratology and narrative generation, and narrative generation systems. The second part presents, in relative detail, components that constitute a systematic study for narrative generation by the author and an integrated narrative generation system of all of the previous attempts.


Author(s):  
Takashi Ogata

This chapter surveys and discusses interdisciplinary approaches to primarily artificial intelligence (AI)-based computational narrative or story generation systems by way of introducing cognitive science, and narratology and related literary theories. The first part of this chapter provides a general description (from the perspective of the research framework of the author) and the second part presents processes, theories, designs, and implementations of narrative generation by the author. In particular, the first part includes an overview of narratology and the relevant literary theories, computational and cognitive theories and techniques related to narratology and narrative generation, and narrative generation systems. The second part presents, in relative detail, components that constitute a systematic study for narrative generation by the author and an integrated narrative generation system of all of the previous attempts.


Author(s):  
Takashi Ogata

This chapter surveys and discusses interdisciplinary approaches to primarily Artificial Intelligence (AI)-based computational narrative or story generation systems by way of introducing cognitive science, and narratology and related literary theories. The first part of this chapter provides a general description (from the perspective of the research framework of the author) and the second part presents processes, theories, designs, and implementations of narrative generation by the author. In particular, the first part includes an overview of narratology and the relevant literary theories, computational and cognitive theories and techniques related to narratology and narrative generation, and narrative generation systems. The second part presents, in relative detail, components that constitute a systematic study for narrative generation by the author and an integrated narrative generation system of all of the previous attempts.


2020 ◽  
Vol 43 ◽  
Author(s):  
Charles P. Davis ◽  
Gerry T. M. Altmann ◽  
Eiling Yee

Abstract Gilead et al.'s approach to human cognition places abstraction and prediction at the heart of “mental travel” under a “representational diversity” perspective that embraces foundational concepts in cognitive science. But, it gives insufficient credit to the possibility that the process of abstraction produces a gradient, and underestimates the importance of a highly influential domain in predictive cognition: language, and related, the emergence of experientially based structure through time.


2003 ◽  
Vol 48 (6) ◽  
pp. 745-748 ◽  
Author(s):  
Michael Mahoney
Keyword(s):  

1995 ◽  
Vol 40 (9) ◽  
pp. 839-840
Author(s):  
James S. Uleman

1985 ◽  
Vol 30 (9) ◽  
pp. 692-693
Author(s):  
Keith Rayner
Keyword(s):  

1985 ◽  
Vol 30 (6) ◽  
pp. 493-494
Author(s):  
Jane Grimshaw
Keyword(s):  

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