The UMASS intelligent home project
Proceedings of the third annual conference on Autonomous Agents
Monitoring deployed agent teams
Proceedings of the fifth international conference on Autonomous agents
Tools for Developing and Monitoring Agents in Distributed Multi-Agent Systems
Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
An Architectural Framework for Integrated Multiagent Planning, Reacting, and Learning
ATAL '00 Proceedings of the 7th International Workshop on Intelligent Agents VII. Agent Theories Architectures and Languages
Multi-Agent Architectures as Organizational Structures
Autonomous Agents and Multi-Agent Systems
On the design of coordination diagnosis algorithms for teams of situated agents
Artificial Intelligence
Matrix-based representation for coordination fault detection: a formal approach
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Matrix-based representation for coordination fault detection: a formal approach
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Detecting disagreements in large-scale multi-agent teams
Autonomous Agents and Multi-Agent Systems
Robust agent teams via socially-attentive monitoring
Journal of Artificial Intelligence Research
On the design of social diagnosis algorithms for multi-agent teams
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A representation for coordination fault detection in large-scale multi-agent systems
Annals of Mathematics and Artificial Intelligence
Diagnosis of coordination failures: a matrix-based approach
Autonomous Agents and Multi-Agent Systems
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Agents working under real world conditions may face an environment capable of changing rapidly from one moment to the next, either through perceived faults, unexpected interactions or adversarial intrusions. To gracefully and efficiently handle such situations, the members of a multi-agent system must be able to adapt, either by evolving internal structures and behavior or repairing or isolating those external influenced believed to be malfunctioning. The first step in achieving adaptability is diagnosis - being able to accurately detect and determine the cause of a fault based on its symptoms. In this paper we examine how domain independent diagnosis plays a role in multi-agent systems, including the information required to support and produce diagnoses. Particular attention is paid to coordination based diagnosis directed by a causal model. Several examples are described in the context of an Intelligent Home environment, and the issue of diagnostic sensitivity versus efficiency is addressed.