Assets Defending Differential Games with Partial Information and Selected Observations

TL;DR

This paper develops a closed-form solution for a linear-quadratic-Gaussian differential game involving partial information, where attacker and defender optimize both control and observation strategies under costs, with decoupled observation decisions.

Contribution

It introduces a novel Nash equilibrium framework for control and observation strategies in a partial information differential game with a closed-form solution.

Findings

Observation strategies can be decoupled and optimized independently.

The asset trajectory does not influence observation choices.

An algorithm effectively computes optimal observation instances.

Abstract

In this paper, we consider a linear-quadratic-Gaussian defending assets differential game (DADG) where the attacker and the defender do not know each other's state information while they know the trajectory of a moving asset. Both players can choose to observe the other player's state information by paying a cost. The defender and the attacker have to craft both control strategies and observation strategies. We obtain a closed-form feedback solution that characterizes the Nash control strategies. We show that the trajectory of the asset does not affect both players' observation choices. Moreover, we show that the observation choices of the defender and the attacker can be decoupled and the Nash observation strategies can be found by solving two independent optimization problems. A set of necessary conditions is developed to characterize the optimal observation instances. Based on the necessary conditions, an effective algorithm is proposed to numerically compute the optimal observation instances. A case study is presented to demonstrate the effectiveness of the optimal observation instances.