Solving the Watchman Route Problem with Heuristic Search

• Published in: The Journal of artificial intelligence research Vol. 75; pp. 747 - 793
• Main Authors: Skyler, Shawn, Atzmon, Dor, Yaffe, Tamir, Felner, Ariel
• Format: Journal Article
• Language: English
• Published: San Francisco AI Access Foundation 01.01.2022
• Subjects: Algorithms; Apexes; Artificial intelligence; Graph theory; Heuristic; Line of sight; Optimization; Searching; Solvers; Traveling salesman problem; Trees (mathematics)
• ISSN: 1076-9757; 1943-5037; 1076-9757; 1943-5037
• DOI: 10.1613/jair.1.13685

This paper solves the Watchman Route Problem (WRP) on a general discrete graph with Heuristic Search. Given a graph, a line-of-sight (LOS) function, and a start vertex, the task is to (offline) find a (shortest) path through the graph such that all vertices in the graph will be visually seen by at least one vertex on the path. WRP is reminiscent but different from graph covering and mapping problems, which are done online on an unknown graph. We formalize WRP as a heuristic search problem and solve it optimally with an A*-based algorithm. We develop a series of admissible heuristics with increasing difficulty and accuracy. Our heuristics abstract the underlying graph into a disjoint line-of-sight graph (GDLS) which is based on disjoint clusters of vertices such that vertices within the same cluster have LOS to the same specific vertex. We use solutions for the Minimum Spanning Tree (MST) and the Traveling Salesman Problem (TSP) of GDLS as admissible heuristics for WRP. We theoretically and empirically investigate these heuristics. Then, we show how the optimal methods can be modified (by intelligently pruning away large sub-trees) to obtain various suboptimal solvers with and without bound guarantees. These suboptimal solvers are much faster and expand fewer nodes than the optimal solver with only minor reduction in the quality of the solution.