Curiosity as filling, compressing, and reconfiguring knowledge networks

Shubhankar P. Patankar; Dale Zhou; Christopher W. Lynn; Jason Z. Kim; Mathieu Ouellet; Harang Ju; Perry Zurn; David M. Lydon-Staley; Dani S. Bassett

arXiv · 2204.01182

Curiosity as filling, compressing, and reconfiguring knowledge networks

Shubhankar P. Patankar·Dale Zhou·Christopher W. Lynn·Jason Z. Kim·Mathieu Ouellet·Harang Ju·Perry Zurn·David M. Lydon-Staley·Dani S. Bassett

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Abstract

Due to the significant role that curiosity plays in our lives, several theoretical constructs, such as the information gap theory and compression progress theory, have sought to explain how we engage in its practice. According to the former, curiosity is the drive to acquire information that is missing from our understanding of the world. According to the latter, curiosity is the drive to construct an increasingly parsimonious mental model of the world. To complement the densification processes inherent to these theories, we propose the conformational change theory, wherein we posit that curiosity results in mental models with marked conceptual flexibility. We formalize curiosity as the process of building a growing knowledge network to quantitatively investigate information gap theory, compression progress theory, and the conformational change theory of curiosity. In knowledge networks, gaps can be identified as topological cavities, compression progress can be quantified using network compressibility, and flexibility can be measured as the number of conformational degrees of freedom. We leverage data acquired from the online encyclopedia Wikipedia to determine the degree to which each theory explains the growth of knowledge networks built by individuals and by collectives. Our findings lend support to a pluralistic view of curiosity, wherein intrinsically motivated information acquisition fills knowledge gaps and simultaneously leads to increasingly compressible and flexible knowledge networks. Across individuals and collectives, we determine the contexts in which each theoretical account may be explanatory, thereby clarifying their complementary and distinct explanations of curiosity. Our findings offer a novel network theoretical perspective on intrinsically motivated information acquisition that may harmonize with or compel an expansion of the traditional taxonomy of curiosity.

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Shubhankar P. Patankar, Dale Zhou, Christopher W. Lynn, Jason Z. Kim, Mathieu Ouellet, Harang Ju, Perry Zurn, David M. Lydon-Staley, Dani S. Bassett. 2022-04-03. Curiosity as filling, compressing, and reconfiguring knowledge networks. https://arxiv.org/abs/2204.01182

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