---
title: "Enhancing Performance of Cooperating Agents in Real-Time Diagnostic Systems"
authors:
  - "Ursula M. Schwuttke"
  - "Alan G. Quan"
doi: ""
url: "https://ijcai.org/proceedings/1993/47"
pdf: "https://ijcai.org/proceedings/1993/0047.pdf"
venue: "Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence"
year: 1993
pages: "332-336"
track: "Distributed AI"
keywords:
---

# Enhancing Performance of Cooperating Agents in Real-Time Diagnostic Systems

Ursula M. Schwuttke, Alan G. Quan

*Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence*, pages 332-336.

## Abstract

We present a data-driven protocol and a supporting architecture for communication among cooperating intelligent agents in real-time diagnostic systems. The system architecture and the exchange of information among agents are based on simplicity of agents, hierarchical organization of agents, and modular non-overlapping division of the problem domain. These features combine to enable efficient diagnosis of complex system failures in real-time environments with high data volumes and moderate failure rates. Preliminary results of the realworld application of this work to the monitoring and diagnosis of complex systems are discussed in the context of NASA's interplanetary mission operations.