  NP-hard problems regularly come up in video games, with interesting
connections to real-world problems. In the game Minecraft, players place
torches on the ground to light up dark areas. Placing them in a way that
minimizes the total number of torches to save resources is far from trivial. In
this paper, we use Quantum Computing to approach this problem. To this end, we
derive a QUBO formulation of the torch placement problem, which we uncover to
be very similar to another NP-hard problem. We employ a solution strategy that
involves learning Lagrangian weights in an iterative process, adding to the
ever growing toolbox of QUBO formulations. Finally, we perform experiments on
real quantum hardware using real game data to demonstrate that our approach
yields good torch placements.
