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Selfish bin covering

Authors: Zhigang Cao 0002; Xiaoguang Yang 0001;

Selfish bin covering

Abstract

In this paper, we address the selfish bin covering problem, which is greatly related both to the bin covering problem, and to the weighted majority game. What we mainly concern is how much the lack of coordination harms the social welfare. Besides the standard PoA and PoS, which are based on Nash equilibrium, we also take into account the strong Nash equilibrium, and several other new equilibria. For each equilibrium, the corresponding PoA and PoS are given, and the problems of computing an arbitrary equilibrium, as well as approximating the best one, are also considered.

16 pages

Related Organizations
Keywords

FOS: Computer and information sciences, Selfish bin covering, price of anarchy, Weighted majority games, price of stability, Nash equilibrium, selfish bin covering, Theoretical Computer Science, Noncooperative games, Price of stability, Computer Science - Computer Science and Game Theory, Combinatorial games, weighted majority games, Price of anarchy, Computer Science(all), Computer Science and Game Theory (cs.GT)

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    popularity
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selected citations
These citations are derived from selected sources.
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!
11
Average
Top 10%
Average
Green
hybrid