  We introduce and analyze greedy equilibria (GE) for the well-known model of
selfish network creation by Fabrikant et al.[PODC'03]. GE are interesting for
two reasons: (1) they model outcomes found by agents which prefer smooth
adaptations over radical strategy-changes, (2) GE are outcomes found by agents
which do not have enough computational resources to play optimally. In the
model of Fabrikant et al. agents correspond to Internet Service Providers which
buy network links to improve their quality of network usage. It is known that
computing a best response in this model is NP-hard. Hence, poly-time agents are
likely not to play optimally. But how good are networks created by such agents?
We answer this question for very simple agents. Quite surprisingly, naive
greedy play suffices to create remarkably stable networks. Specifically, we
show that in the SUM version, where agents attempt to minimize their average
distance to all other agents, GE capture Nash equilibria (NE) on trees and that
any GE is in 3-approximate NE on general networks. For the latter we also
provide a lower bound of 3/2 on the approximation ratio. For the MAX version,
where agents attempt to minimize their maximum distance, we show that any
GE-star is in 2-approximate NE and any GE-tree having larger diameter is in
6/5-approximate NE. Both bounds are tight. We contrast these positive results
by providing a linear lower bound on the approximation ratio for the MAX
version on general networks in GE. This result implies a locality gap of
$\Omega(n)$ for the metric min-max facility location problem, where n is the
number of clients.
