Multiagent Simple Temporal Problem: The Arc-Consistency Approach

TL;DR

This paper introduces an arc-consistency based method for solving the Multiagent Simple Temporal Problem (MaSTP), which is efficient, preserves agent privacy, and outperforms existing approaches in empirical tests.

Contribution

The paper presents a novel arc-consistency approach for MaSTP that is both efficient and privacy-preserving, extending the classical STP solution methods.

Findings

AC-based algorithms are more efficient than existing methods

The approach does not violate agent privacy

Empirical results show significant performance improvements

Abstract

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.