Optimal Communication and Control Strategies for a Multi-Agent System in the Presence of an Adversary

TL;DR

This paper develops a strategic framework for multi-agent systems to optimize control and communication in the presence of an adversary, modeling interactions as a stochastic zero-sum game to derive robust strategies.

Contribution

It introduces a novel game-theoretic approach for joint control and communication strategies in adversarial multi-agent systems, with structural results for computational tractability.

Findings

Characterized a min-max control and communication strategy for the team.

Provided structural results to simplify strategy computation.

Demonstrated robustness of strategies against adversarial actions.

Abstract

We consider a multi-agent system in which a decentralized team of agents controls a stochastic system in the presence of an adversary. Instead of committing to a fixed information sharing protocol, the agents can strategically decide at each time whether to share their private information with each other or not. The agents incur a cost whenever they communicate with each other and the adversary may eavesdrop on their communication. Thus, the agents in the team must effectively coordinate with each other while being robust to the adversary's malicious actions. We model this interaction between the team and the adversary as a stochastic zero-sum game where the team aims to minimize a cost while the adversary aims to maximize it. Under some assumptions on the adversary's capabilities, we characterize a min-max control and communication strategy for the team. We supplement this characterization with several structural results that can make the computation of the min-max strategy more tractable.