Mobile Target Search with Imperfect Perception: A Partially Observable Stochastic Game Theoretical Approach

2026-06-18

AI Summary

This work addresses the adversarial interaction problem of searching for and evading a mobile target under perceptual limitations—such as sensor constraints, interference, or noise—by modeling it as a partially observable stochastic game (POSG) and introducing the notion of detectability. To overcome the limitations of traditional POMDP approaches when confronting intelligent adversarial targets, the authors propose a server-assisted distributed algorithm that integrates an aggregative potential game structure with a KL divergence–based reduction method, analyzed through stochastic recursive techniques. Theoretical analysis and numerical simulations validate the effectiveness of the proposed detectability criterion, demonstrating efficient and reliable search performance against intelligent mobile targets in perception-uncertain environments.

Abstract

This paper investigates mobile target search under imperfect perceptions caused by sensor limitations, malicious jamming, or communication noise. Searchers and targets operate in a grid-shaped area with bounded mobility, leading to a dynamic interplay between search and evasion. To capture this adversarial interaction under imperfect perceptions, we adopt the partially observable stochastic game (POSG) approach, which generalizes partially observable Markov decision processes (POMDPs) by incorporating target intelligence. To handle false alarms and missed detections caused by perceptual uncertainties, we propose a novel detectability concept to determine whether a search strategy guarantees eventual detection, and provide sufficient detectability criteria based on stochastic recurrence analysis. We further develop a server-assisted distributed algorithm that utilizes the aggregative potential game structure for searchers and a KL-divergence-based reduction for target prediction. Numerical simulations validate the effectiveness of the proposed algorithm and support the detectability analysis.

Problem

• mobile target search
• imperfect perception
• partially observable stochastic game
• detectability
• adversarial interaction

Innovation

• Partially Observable Stochastic Game
• Detectability
• Aggregative Potential Game
• KL-divergence-based Reduction
• Stochastic Recurrence Analysis