  Context. Strong gravitationally lensed quasars are among the most interesting
and useful observable extragalactic phenomena. Because their study constitutes
a unique tool in various fields of astronomy, they are highly sought, not
without difficulty. Indeed, even in this era of all-sky surveys, their
recognition remains a great challenge, with barely a few hundred currently
known systems. Aims. In this work we aim to detect new strongly lensed quasar
candidates in the recently published Gaia Data Release 2 (DR2), which is the
highest spatial resolution astrometric and photometric all-sky survey,
attaining effective resolutions from 0.4" to 2.2". Methods. We cross-matched a
merged list of quasars and candidates with the Gaia DR2 and found 1,839,143
counterparts within 0.5". We then searched matches with more than two Gaia DR2
counterparts within 6". We further narrowed the resulting list using astrometry
and photometry compatibility criteria between the Gaia DR2 counterparts. A
supervised machine learning method, Extremely Randomized Trees, is finally
adopted to assign to each remaining system a probability of being lensed.
Results. We report the discovery of three quadruply-imaged quasar candidates
that are fully detected in Gaia DR2. These are the most promising new quasar
lens candidates from Gaia DR2 and a simple singular isothermal ellipsoid lens
model is able to reproduce their image positions to within $\sim$1 mas. This
letter demonstrates the gravitational lens discovery potential of Gaia.
