An algorithm for a fairer and better voting system
Gabriel-Claudiu Grama

TL;DR
This paper introduces a novel ranked voting algorithm designed to improve fairness and accuracy in selecting the best candidate, demonstrating superior performance over traditional voting methods through AI-based simulations.
Contribution
The paper presents a new voting algorithm that outperforms existing methods like Instant-Runoff and FPTP, supported by AI simulations and comparative analysis.
Findings
The new algorithm outperforms traditional voting systems under certain conditions.
Simulations show improved fairness and representation.
The approach supports the wisdom of crowds in decision-making.
Abstract
The major finding, of this article, is an ensemble method, but more exactly, a novel, better ranked voting system (and other variations of it), that aims to solve the problem of finding the best candidate to represent the voters. We have the source code on GitHub, for making realistic simulations of elections, based on artificial intelligence for comparing different variations of the algorithm, and other already known algorithms. We have convincing evidence that our algorithm is better than Instant-Runoff Voting, Preferential Block Voting, Single Transferable Vote, and First Past The Post (if certain, natural conditions are met, to support the wisdom of the crowds). By also comparing with the best voter, we demonstrated the wisdom of the crowds, suggesting that democracy (distributed system) is a better option than dictatorship (centralized system), if those certain, natural…
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Taxonomy
TopicsGame Theory and Voting Systems · Cryptography and Data Security · Distributed systems and fault tolerance
