On-the-fly Adaptation of Patrolling Strategies in Changing Environments
Tom\'a\v{s} Br\'azdil, David Kla\v{s}ka, Anton\'in Ku\v{c}era, V\'it, Musil, Petr Novotn\'y, Vojt\v{e}ch \v{R}eh\'ak

TL;DR
This paper presents a framework for real-time adaptation of patrolling strategies in dynamic environments, ensuring quick strategy updates without security risks, and is validated through experiments.
Contribution
It introduces a novel approach for instant strategy switching in changing environments with mechanisms to detect and mitigate security risks.
Findings
Framework effectively adapts strategies in real-time
Mechanisms reduce security risks during strategy transitions
Experimental results demonstrate robustness and efficiency
Abstract
We consider the problem of efficient patrolling strategy adaptation in a changing environment where the topology of Defender's moves and the importance of guarded targets change unpredictably. The Defender must instantly switch to a new strategy optimized for the new environment, not disrupting the ongoing patrolling task, and the new strategy must be computed promptly under all circumstances. Since strategy switching may cause unintended security risks compromising the achieved protection, our solution includes mechanisms for detecting and mitigating this problem. The efficiency of our framework is evaluated experimentally.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimization and Search Problems · Distributed Control Multi-Agent Systems · Robotic Path Planning Algorithms
