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

Paul Brewer1, Jeremy Juybari2,3, Raymond Moberly2
1Economic and Financial Technology Consulting LLC, Ooltewah, USA
2Faster Logic LLC, San Diego, USA
3Department of Electrical and Computer Engineering, University of Maine, Orono, USA

Tóm tắt

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.

Tài liệu tham khảo

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