Minimax Multi-Agent Persistent Monitoring of a Network System

TL;DR

This paper addresses optimal persistent monitoring of multiple targets in a network by a mobile agent, proposing a novel approach to sequence and dwell-time optimization to minimize maximum target uncertainty over time.

Contribution

It introduces a new efficient algorithm for optimal dwell-time allocation and a greedy heuristic for sequence optimization in persistent monitoring tasks.

Findings

The optimal dwelling time allocation equalizes peak uncertainty across targets.

The proposed algorithms outperform baseline methods in numerical simulations.

The approach effectively reduces maximum target uncertainty in network monitoring scenarios.

Abstract

We investigate the problem of optimally observing a finite set of targets using a mobile agent over an infinite time horizon. The agent is tasked to move in a network-constrained structure to gather information so as to minimize the worst-case uncertainty about the internal states of the targets. To do this, the agent has to decide its sequence of target-visits and the corresponding dwell-times at each visited target. For a given visiting sequence, we prove that in an optimal dwelling time allocation the peak uncertainty is the same among all the targets. This allows us to formulate the optimization of dwelling times as a resource allocation problem and to solve it using a novel efficient algorithm. Next, we optimize the visiting sequence using a greedy exploration process, using heuristics inspired by others developed in the context of the traveling salesman problem. Numerical results are included to illustrate the contributions.