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On Parameterized Complexity of Liquid Democracy

Authors: Palash Dey; Arnab Maiti; Amatya Sharma;

On Parameterized Complexity of Liquid Democracy

Abstract

In liquid democracy, each voter either votes herself or delegates her vote to some other voter. This gives rise to what is called a delegation graph. To decide the voters who eventually votes along with the subset of voters whose votes they give, we need to resolve the cycles in the delegation graph. This gives rise to the Resolve Delegation problem where we need to find an acyclic sub-graph of the delegation graph such that the number of voters whose votes they give is bounded above by some integer ��. Putting a cap on the number of voters whose votes a voter gives enable the system designer restrict the power of any individual voter. The Resolve Delegation problem is already known to be NP-hard. In this paper we study the parameterized complexity of this problem. We show that Resolve Delegation is para-NP-hard with respect to parameters ��, number of sink nodes and the maximum degree of the delegation graph. We also show that Resolve Delegation is W[1]-hard even with respect to the treewidth of the delegation graph. We complement our negative results by exhibiting FPT algorithms with respect to some other parameters. We finally show that a related problem, which we call Resolve Fractional Delegation, is polynomial time solvable.

Submitted to 7th Annual International Conference on Algorithms and Discrete Applied Mathematics [CALDAM 2021]

Keywords

FOS: Computer and information sciences, B.6, B.7, Computational Complexity (cs.CC), 68Q27, 05C90, Computer Science - Computational Complexity, Computer Science - Computers and Society, Computer Science - Computer Science and Game Theory, Computer Science - Data Structures and Algorithms, Computers and Society (cs.CY), Data Structures and Algorithms (cs.DS), B.6; B.7; F.1.3, F.1.3, Computer Science and Game Theory (cs.GT)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green