Model-Based Diagnosis of Multi-Agent Systems: A Survey

Meir Kalech, Avraham Natan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

As systems involving multiple agents are increasingly deployed, there is a growing need to diagnose failures in such systems. Model-Based Diagnosis (MBD) is a well known AI technique to diagnose faults in systems. In this approach, a model of the diagnosed system is given, and the real system is observed. A failure is announced when the real system's output contradicts the model's expected output. The model then is used to deduce the defective components that explain the unexpected observation. MBD has been increasingly being deployed in distributed and multi-agent systems. In this survey, we summarize twenty years of research in the field of model-based diagnosis algorithms for MAS diagnosis. We depict three attributes that should be considered when examining MAS diagnosis: (1) The objective of the diagnosis. Either diagnosing faults in the MAS plans or diagnosing coordination faults. (2) Centralized vs. distributed. The diagnosis method could be applied either by a centralized agent or by the agents in a distributed manner. (3) Temporal vs. non-temporal. Temporal diagnosis is used to diagnose the MAS's temporal behaviors, whereas non-temporal diagnosis is used to diagnose the conduct based on a single observation. We survey diverse studies in MBD of MAS based on these attributes, and provide novel research challenges in this field for the AI community.

Original languageEnglish
Title of host publicationAAAI
PublisherAssociation for the Advancement of Artificial Intelligence
Pages12334-12341
Number of pages8
Volume36
ISBN (Electronic)1577358767, 9781577358763
StatePublished - 28 Jun 2022
Event36th AAAI Conference on Artificial Intelligence, AAAI 2022 - Virtual, Online
Duration: 22 Feb 20221 Mar 2022

Publication series

NameProceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022
Volume36

Conference

Conference36th AAAI Conference on Artificial Intelligence, AAAI 2022
CityVirtual, Online
Period22/02/221/03/22

Keywords

  • Model-Based Diagnosis
  • Multi-Agent Systems
  • Constraints

ASJC Scopus subject areas

  • Artificial Intelligence

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