Modifying Optimal SAT-based Approach to Multi-agent Path-finding Problem
  to Suboptimal Variants
  In multi-agent path finding (MAPF) the task is to find non-conflicting paths
for multiple agents. In this paper we focus on finding suboptimal solutions for
MAPF for the sum-of-costs variant. Recently, a SAT-based approached was
developed to solve this problem and proved beneficial in many cases when
compared to other search-based solvers. In this paper, we present SAT-based
unbounded- and bounded-suboptimal algorithms and compare them to relevant
algorithms. Experimental results show that in many case the SAT-based solver
significantly outperforms the search-based solvers.
