  We develop and test an automated technique to model the dynamics of
interacting galaxy pairs. We use Identikit (Barnes & Hibbard 2009, Barnes 2011)
as a tool for modeling and matching the morphology and kinematics of the
interacting pairs of equal-mass galaxies. In order to reduce the effect of
subjective human judgement, we automate the selection of phase-space regions
used to match simulations to data, and we explore how selection of these
regions affects the random uncertainties of parameters in the best-fit model.
In this work, we use an independent set of GADGET SPH simulations as input data
to determine the systematic bias in the measured encounter parameters based on
the known initial conditions of these simulations. We test both cold gas and
young stellar components in the GADGET simulations to explore the effect of
choosing HI vs. H$\alpha$ as the line of sight velocity tracer. We find that we
can group the results into tests with good, fair, and poor convergence based on
the distribution of parameters of models close to the best-fit model. For tests
with good and fair convergence, we rule out large fractions of parameter space
and recover merger stage, eccentricity, pericentric distance, viewing angle,
and initial disc orientations within 3$\sigma$ of the correct value. All of
tests on prograde-prograde systems have either good or fair convergence. The
results of tests on edge-on discs are less biased than face-on tests.
Retrograde and polar systems do not converge and may require constraints from
regions other than the tidal tails and bridges.
