Combining deliberate study and heuristics to form opinions on interconnected questions

Ruijie Wang, Yuhao Zhou and Matúš Medo

Chaos, Solitons & Fractals, 2025, vol. 199, issue P1

Abstract: The ever-increasing complexity of the world around us challenges our ability to understand it. We study a model where an individual forms opinions about many interconnected questions. This model was shown to be challenging for a boundedly rational agent. We extend it by assuming that the individual combines a targeted study of some questions and various heuristics for the remaining ones. We find that the highest opinion accuracy is generally achieved when neither one question is studied particularly well nor when many questions are studied a little. Despite big differences in accuracy between the considered heuristics, the optimal number of questions in which the study budget is invested grows linearly with the budget for all of them. The study budget necessary to achieve the desired opinion accuracy exhibits a simple scaling with the total number of questions. In this way, we exemplify efficient learning in a complex system using simple heuristics.

Keywords: Opinion formation; Signed networks; Learning; Heuristics (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:199:y:2025:i:p1:s0960077925005752

DOI: 10.1016/j.chaos.2025.116562

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