Escape Sensing Games: Detection-vs-Evasion in Security Applications

TL;DR

This paper introduces Escape Sensing Games, a new class of strategic target arrangement games for security, analyzing their computational complexity and proposing heuristic algorithms for practical solutions.

Contribution

It presents the novel concept of ESGs, explores their computational hardness, and develops heuristic algorithms validated through extensive experiments.

Findings

Computing best responses and equilibria in ESGs is NP-hard.

Heuristic algorithms can effectively approximate solutions.

Extensive computational experiments demonstrate algorithm performance.

Abstract

Traditional game-theoretic research for security applications primarily focuses on the allocation of external protection resources to defend targets. This work puts forward the study of a new class of games centered around strategically arranging targets to protect them against a constrained adversary, with motivations from varied domains such as peacekeeping resource transit and cybersecurity. Specifically, we introduce Escape Sensing Games (ESGs). In ESGs, a blue player manages the order in which targets pass through a channel, while her opponent tries to capture the targets using a set of sensors that need some time to recharge after each activation. We present a thorough computational study of ESGs. Among others, we show that it is NP-hard to compute best responses and equilibria. Nevertheless, we propose a variety of effective (heuristic) algorithms whose quality we demonstrate in extensive computational experiments.