Mutex Graphs and Multicliques: Reducing Grounding Size for Planning
  We present an approach to representing large sets of mutual exclusions, also
known as mutexes or mutex constraints. These are the types of constraints that
specify the exclusion of some properties, events, processes, and so on. They
are ubiquitous in many areas of applications. The size of these constraints for
a given problem can be overwhelming enough to present a bottleneck for the
solving efficiency of the underlying solver. In this paper, we propose a novel
graph-theoretic technique based on multicliques for a compact representation of
mutex constraints and apply it to domain-independent planning in ASP. As
computing a minimum multiclique covering from a mutex graph is NP-hard, we
propose an efficient approximation algorithm for multiclique covering and show
experimentally that it generates substantially smaller grounding size for mutex
constraints in ASP than the previously known work in SAT.
