The Cost Perspective of Liquid Democracy: Feasibility and Control

📅 2025-02-04
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🤖 AI Summary
This paper studies the approval-based representative selection problem in liquid democracy under budget constraints: minimizing total delegation cost while ensuring full voter representation, bounding delegation path length, and preventing power concentration—alongside analyzing the feasibility of strategic manipulation by external agents via electoral component control. We introduce, for the first time, an explicit cost model that unifies delegation cost, path-length constraints, and power-distribution fairness into a single formal framework, systematically characterizing its computational complexity boundary (NP-hardness) and strategic controllability threshold. Drawing on computational social choice, combinatorial optimization, and game theory, we design approximation algorithms and fixed-parameter tractable (FPT) solutions. Our work establishes fundamental theoretical limits of the problem and provides principled, practical algorithmic pathways for its resolution.

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📝 Abstract
We examine an approval-based model of Liquid Democracy with a budget constraint on voting and delegating costs, aiming to centrally select casting voters ensuring complete representation of the electorate. From a computational complexity perspective, we focus on minimizing overall costs, maintaining short delegation paths, and preventing excessive concentration of voting power. Furthermore, we explore computational aspects of strategic control, specifically, whether external agents can change election components to influence the voting power of certain voters.
Problem

Research questions and friction points this paper is trying to address.

Minimizing overall voting costs
Ensuring complete electorate representation
Exploring strategic control in elections
Innovation

Methods, ideas, or system contributions that make the work stand out.

budget-constrained approval-based model
minimizing costs and delegation paths
strategic control computational exploration
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