  The Simple Temporal Problem (STP) is a fundamental temporal reasoning problem
and has recently been extended to the Multiagent Simple Temporal Problem
(MaSTP). In this paper we present a novel approach that is based on enforcing
arc-consistency (AC) on the input (multiagent) simple temporal network. We show
that the AC-based approach is sufficient for solving both the STP and MaSTP and
provide efficient algorithms for them. As our AC-based approach does not impose
new constraints between agents, it does not violate the privacy of the agents
and is superior to the state-of-the-art approach to MaSTP. Empirical
evaluations on diverse benchmark datasets also show that our AC-based
algorithms for STP and MaSTP are significantly more efficient than existing
approaches.
