  A new and automated method is presented for the analysis of high-resolution
absorption spectra. Three established numerical methods are unified into one
"artificial intelligence" process: a genetic algorithm (GVPFIT); non-linear
least-squares with parameter constraints (VPFIT); and Bayesian Model Averaging
(BMA).
  The method has broad application but here we apply it specifically to the
problem of measuring the fine structure constant at high redshift. For this we
need objectivity and reproducibility. GVPFIT is also motivated by the
importance of obtaining a large statistical sample of measurements of
$\Delta\alpha/\alpha$. Interactive analyses are both time consuming and complex
and automation makes obtaining a large sample feasible.
  In contrast to previous methodologies, we use BMA to derive results using a
large set of models and show that this procedure is more robust than a human
picking a single preferred model since BMA avoids the systematic uncertainties
associated with model choice.
  Numerical simulations provide stringent tests of the whole process and we
show using both real and simulated spectra that the unified automated fitting
procedure out-performs a human interactive analysis. The method should be
invaluable in the context of future instrumentation like ESPRESSO on the VLT
and indeed future ELTs.
  We apply the method to the $z_{abs} = 1.8389$ absorber towards the $z_{em} =
2.145$ quasar J110325-264515. The derived constraint of $\Delta\alpha/\alpha =
3.3 \pm 2.9 \times 10^{-6}$ is consistent with no variation and also consistent
with the tentative spatial variation reported in Webb et al (2011) and King et
al (2012).
