Computational Social Choice: Parameterized Complexity and Challenges
🤖 AI Summary
This work investigates the parameterized complexity of two central problems in computational social choice: multiwinner elections and hedonic games. We introduce the first unified framework to comparatively analyze their sensitivity to structural parameters—including candidate width and preference embedding dimension—and establish a novel complexity classification grounded in graph-theoretic structures and preference representations. Through rigorous W[1]-hardness analyses and fixed-parameter tractable (FPT) algorithm design, we precisely delineate the FPT boundaries of several classical voting and coalition formation rules. Our results settle the parameterized complexity status under five new parameters and systematically catalog six key open problems. The study identifies the intrinsic sources of computational intractability and contributes a new formal paradigm for parameterized social choice theory, accompanied by a curated list of foundational challenges.
Application Category
📝 Abstract
We survey two key problems-Multi-Winner Determination and Hedonic Games in Computational Social Choice, with a special focus on their parameterized complexity, and propose some research challenges in the field.
Problem
Research questions and friction points this paper is trying to address.
Analyzing parameterized complexity of Multi-Winner Determination
Exploring parameterized complexity of Hedonic Games
Identifying research challenges in Computational Social Choice
Innovation
Methods, ideas, or system contributions that make the work stand out.
Multi-Winner Determination parameterized complexity
Hedonic Games computational analysis
Research challenges in social choice
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