A Framework to Control Emergent Survivability of Multi Agent Systems

TLDR

Multi‑agent systems are increasingly used for mission‑critical applications, but their distributed nature makes designing survivable, resource‑constrained systems challenging; however, their flexibility allows runtime resource shifting among security, robustness, and primary functions. This work develops an algebra to compute overall survivability from multiple success dimensions and proposes a control infrastructure that adapts resources at runtime to maximize system survivability. The authors implement the infrastructure on the Cougaar agent architecture and build a military logistics application that demonstrates survivability in chaotic environments. Performance assessment shows the application maintains survivability under chaotic conditions, suggesting the framework is promising for future deployed DMAS.

Abstract

As the science of multi-agent systems matures, many developers are looking to deploy mission critical applications on distributed multi-agent systems (DMAS). Due to their distributed nature, designing survivable resource constrained DMAS is a serious challenge. Fortunately, the intrinsic flexibility of DMAS allows them to shift resources at runtime between dimensions of functionality such as security, robustness, and the primary application. In this paper we present an algebra for computing overall survivability from these dimensions of success, and a control infrastructure that leverages these degrees of freedom to make run-time adaptations at multiple hierarchical levels to maximize overall system survivability. We have implemented this survivability control infrastructure on the Cougaar agent architecture, and built a military logistics application that can survive in chaotic environments. Finally, we present results from assessing the performance of this application, and discuss the implications for future deployed DMAS.