Parameterized Complexity of Candidate Nomination for Elections based on Positional Scoring Rules

Schlotter, Ildikó and Cechlárová, Katarína and Trellová, Diana (2024) Parameterized Complexity of Candidate Nomination for Elections based on Positional Scoring Rules. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 38. No.-28. ISSN 1387-2532 (print); 1573-7454 (online)

Preview

Text s10458-024-09658-5.pdf Available under License Creative Commons Attribution. Download (2MB) | Preview

Abstract

Consider elections where the set of candidates is partitioned into parties, and each party must nominate exactly one candidate. The Possible President problem asks whether some candidate of a given party can become the unique winner of the election for some nominations from other parties. We perform a multivariate computational complexity analysis of Possible President for several classes of elections based on positional scoring rules. We consider the following parameters: the size of the largest party, the number of parties, the number of voters and the number of voter types. We provide a complete computational map of P ossible P resident in the sense that for each choice of the four possible parameters as (i) constant, (ii) parameter, or (iii) unbounded, we classify the computational complexity of the resulting problem as either polynomial-time solvable or -complete, and for parameterized versions as either fixed-parameter tractable or [1]-hard with respect to the parameters considered.

Actions (login required)

Edit Item