Affiliation:
1. Department of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology
2. Department of Computer Science & Engineering University of California San Diego
3. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology
Abstract
AbstractGreat storytelling takes us on a journey the way ordinary reality rarely does. But what exactly do we mean by this “journey?” Recently, literary theorist Karin Kukkonen proposed that storytelling is “probability design:” the art of giving an audience pieces of information bit by bit, to craft the journey of their changing beliefs about the fictional world. A good “probability design” choreographs a delicate dance of certainty and surprise in the reader's mind as the story unfolds from beginning to end. In this paper, we computationally model this conception of storytelling. Building on the classic Bayesian inverse planning model of human social cognition, we treat storytelling as inverse inverse planning: the task of choosing actions to manipulate an inverse planner's inferences, and therefore a human audience's beliefs. First, we use an inverse inverse planner to depict social and physical situations, and present behavioral studies indicating that inverse inverse planning produces more expressive behavior than ordinary “naïve planning.” Then, through a series of examples, we demonstrate how inverse inverse planning captures many storytelling elements from first principles: character, narrative arcs, plot twists, irony, flashbacks, and deus ex machina are all naturally encoded in the flexible language of probability design.
Funder
National Natural Science Foundation of China
Office of Naval Research
Subject
Artificial Intelligence,Cognitive Neuroscience,Human-Computer Interaction,Linguistics and Language,Experimental and Cognitive Psychology
Cited by
1 articles.
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1. Storytelling as Inverse Inverse Planning;Topics in Cognitive Science;2023-11-14