A comparison of zero- and minimal-intelligence agendas in majority-rule voting models

Paul Brewer (), Jeremy Juybari () and Raymond Moberly
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Paul Brewer: Economic and Financial Technology Consulting LLC
Jeremy Juybari: Faster Logic LLC
Raymond Moberly: Faster Logic LLC

Journal of Economic Interaction and Coordination, 2024, vol. 19, issue 3, No 2, 403-437

Abstract: Abstract Emergent behavior in repeated collective decisions of minimally intelligent agents—who at each step in time invoke majority rule to choose between a status quo and a random challenge—can manifest through the long-term stationary probability distributions of a Markov chain. We use this known technique to compare two kinds of voting agendas: a zero-intelligence agenda that chooses the challenger uniformly at random and a minimally intelligent agenda that chooses the challenger from the union of the status quo and the set of winning challengers. We use Google Co-Lab’s GPU accelerated computing environment to compute stationary distributions for some simple examples from spatial-voting and budget-allocation scenarios. We find that the voting model using the zero-intelligence agenda converges more slowly, but in some cases to better outcomes.

Keywords: Emergent behavior; Zero and minimally intelligent agents; Majority rule; Spatial voting; Budget allocation; Limits of artificial intelligence; Markov chain applications (search for similar items in EconPapers)
JEL-codes: C63 D71 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11403-023-00387-8

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