Socially conscious stability for tiered coalition formation games

Nathan Arnold, Sarah Snider,Judy Goldsmith

ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE(2023)

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摘要
We investigate Tiered Coalition Formation Games (TCFGs), a cooperative game inspired by the stratification of Pokémon on the fan website, Smogon. It is known that, under match-up oriented preferences, Nash and core stability are equivalent. We previously introduced a notion of socially conscious stability for TCFGs, and introduced a game variant with fixed k -length tier lists. In this work we show that in tier lists under match-up oriented preferences, socially conscious stability is equivalent to Nash stability and to core stability, but in k -tier lists, the three stability notions are distinct. We also give a necessary condition for tier list stability in terms of robustness (the minimum in-tier utility of an agent). We introduce a notion of approximate Nash stability and approximately socially conscious stability, and provide experiments on the empirical run time of our k -tier local search algorithm, and the performance of our algorithms for generating approximately socially consciously stable tier lists.
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