  We consider isomorphism properties of infinite random geometric graphs
defined over a variety of metrics. In previous work, it was shown that for
$\mathbb{R}^n$ with the $L_{\infty}$-metric, the infinite random geometric
graph is, with probability 1, unique up to isomorphism. However, in the case
$n=2$ this is false with either of the $L_2$-metric. We generalize this result
to a large family of metrics induced by norms. Within this class of metric
spaces, we show that the infinite geometric graph is not unique up to
isomorphism if it has the new property which we name truncating: each
step-isometry from a dense set to itself is an isometry. As a corollary, we
derive that the infinite random geometric graph defined in $L_p$ space is not
unique up to isomorphism with probability 1 for all finite $p>1.$
