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Scalable Algorithms with Provable Optimality Bounds for the Multiple Watchman Route Problem

  • Srikar Gouru
  • , Ariel Felner
  • , Jiaoyang Li
  • Carnegie Mellon University
  • Ben-Gurion University of the Negev

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we tackle the Multiple Watchman Route Problem (MWRP), which aims to find a set of paths that M watchmen can follow such that every location on the map can be seen by at least one watchman. First, we propose multiple methods to reduce the state space over which a search needs to be conducted by pruning map areas that are guaranteed to be seen en route to other areas. Next, we introduce MWRP-CP3, an efficient optimal planner that combines these methods with techniques that improve the quality and calculation time of existing heuristics. We present several suboptimal algorithms with bounds on solution quality, including MxWA*, a general variant of weighted A* for makespan problems. We also present anytime variations of our suboptimal algorithms, as well as techniques to improve an existing suboptimal solution by solving multiple decomposed sub-problems. We show that MWRP-CP3 can reduce the search space by more than 95% and runs more than 200× faster than existing optimal algorithms on 2D grid maps. We also show that our suboptimal algorithms solve maps 3× larger than those solvable by MWRP-CP3 . See mwrp-cp3.github.io for the open source codebase and video demonstrations.

Original languageEnglish
Title of host publicationProceedings International Conference on Automated Planning and Scheduling, ICAPS
EditorsAmanda Coles, Wheeler Ruml, Sandhya Saisubramanian
PublisherAssociation for the Advancement of Artificial Intelligence
Pages95-103
Number of pages9
Edition1
ISBN (Print)9781577359104
DOIs
StatePublished - 2026
Externally publishedYes
Event36th International Conference on Automated Planning and Scheduling, ICAPS 2026 - Dublin, Ireland
Duration: 27 Jun 20262 Jul 2026

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Number1
Volume36
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference36th International Conference on Automated Planning and Scheduling, ICAPS 2026
Country/TerritoryIreland
CityDublin
Period27/06/262/07/26

Bibliographical note

Publisher Copyright:
© 2026, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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