Stability of networks under horizon-K farsightedness
提出了远视程度为K的稳定集概念，研究玩家远视程度对网络稳定性的影响，并分析了不同远视程度下网络的存在性、唯一性和效率。
We introduce the concept of a horizon-K farsighted set to study the influence of the degree of farsightedness on network stability. The concept generalizes existing concepts where all players are either fully myopic or fully farsighted. A set of networks $$G_{K}$$ is a horizon-K farsighted set if three conditions are satisfied. First, external deviations should be horizon-K deterred. Second, from any network outside of $$G_{K}$$ there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ . Third, there is no proper subset of $$G_{K}$$ satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ is always unique. For generic allocation rules, the set $$G_{1}$$ always contains a horizon-K farsighted set for any K. We provide easy to verify conditions for a set of networks to be a horizon-K farsighted set, and we consider the efficiency of networks in horizon-K farsighted sets. We discuss the effects of players with different horizons in an example of criminal networks.