Stability of networks under horizon-K farsightedness

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 $$G_{K}$$ 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 $$G_{K}$$ G K there is a sequence of farsighted improving paths of length smaller than or equal to K leading to some network in $$G_{K}$$ G K . Third, there is no proper subset of $$G_{K}$$ G K satisfying the first two conditions. We show that a horizon-K farsighted set always exists and that the horizon-1 farsighted set $$G_{1}$$ G 1 is always unique. For generic allocation rules, the set $$G_{1}$$ 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.(This abstract was borrowed from another version of this item.)