Social comparison for failure detection and recovery

Gal A. Kaminka; Milind Tambe

doi:10.1007/bfb0026755

Social comparison for failure detection and recovery

Gal A. Kaminka, Milind Tambe

University of Southern California

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Plan execution monitoring in dynamic and uncertain domains is an important and difficult problem. Multi-agent environments exacerbate this problem, given that interacting and coordinated activities of multiple agents are to be monitored. Previous approaches to this problem do not detect certain classes of failures, are inflexible, and are hard to scalp up. We present a novel approach, SOCFAD, to failure detection and recovery in multi-agent settings. SOCFAD is inspired by Social Comparison Theory from social psychology and includes the following key novel concepts: (a) utilizing other agents in the environment as information sources for failure detection, (b) a detection and repair method for previously undetectable failures using abductive inference based on other agents' beliefs, and (c) a decision-theoretic approach to selecting the information acquisition medium. An analysis of SOCFAD is presented, showing that the new method is complementary to previous approaches in terms of classes of failures detected.

Original language	English
Title of host publication	Intelligent Agents IV
Subtitle of host publication	Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings
Editors	Munindar P. Singh, Anand Rao, Michael J. Wooldridge
Publisher	Springer Verlag
Pages	127-141
Number of pages	15
ISBN (Print)	3540641629, 9783540641629
DOIs	https://doi.org/10.1007/bfb0026755
State	Published - 1998
Externally published	Yes
Event	4th International Workshop on Agent Theories, Architectures, and Languages, ATAL 1997 - Providence, United States Duration: 24 Jul 1997 → 26 Jul 1997

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1365
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Workshop on Agent Theories, Architectures, and Languages, ATAL 1997
Country/Territory	United States
City	Providence
Period	24/07/97 → 26/07/97

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1998.

Access to Document

10.1007/bfb0026755

Cite this

Kaminka, G. A., & Tambe, M. (1998). Social comparison for failure detection and recovery. In M. P. Singh, A. Rao, & M. J. Wooldridge (Eds.), Intelligent Agents IV: Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings (pp. 127-141). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1365). Springer Verlag. https://doi.org/10.1007/bfb0026755

Kaminka, Gal A. ; Tambe, Milind. / Social comparison for failure detection and recovery. Intelligent Agents IV: Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings. editor / Munindar P. Singh ; Anand Rao ; Michael J. Wooldridge. Springer Verlag, 1998. pp. 127-141 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Plan execution monitoring in dynamic and uncertain domains is an important and difficult problem. Multi-agent environments exacerbate this problem, given that interacting and coordinated activities of multiple agents are to be monitored. Previous approaches to this problem do not detect certain classes of failures, are inflexible, and are hard to scalp up. We present a novel approach, SOCFAD, to failure detection and recovery in multi-agent settings. SOCFAD is inspired by Social Comparison Theory from social psychology and includes the following key novel concepts: (a) utilizing other agents in the environment as information sources for failure detection, (b) a detection and repair method for previously undetectable failures using abductive inference based on other agents' beliefs, and (c) a decision-theoretic approach to selecting the information acquisition medium. An analysis of SOCFAD is presented, showing that the new method is complementary to previous approaches in terms of classes of failures detected.",

author = "Kaminka, {Gal A.} and Milind Tambe",

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year = "1998",

doi = "10.1007/bfb0026755",

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Kaminka, GA & Tambe, M 1998, Social comparison for failure detection and recovery. in MP Singh, A Rao & MJ Wooldridge (eds), Intelligent Agents IV: Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1365, Springer Verlag, pp. 127-141, 4th International Workshop on Agent Theories, Architectures, and Languages, ATAL 1997, Providence, United States, 24/07/97. https://doi.org/10.1007/bfb0026755

Social comparison for failure detection and recovery. / Kaminka, Gal A.; Tambe, Milind.
Intelligent Agents IV: Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings. ed. / Munindar P. Singh; Anand Rao; Michael J. Wooldridge. Springer Verlag, 1998. p. 127-141 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1365).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Plan execution monitoring in dynamic and uncertain domains is an important and difficult problem. Multi-agent environments exacerbate this problem, given that interacting and coordinated activities of multiple agents are to be monitored. Previous approaches to this problem do not detect certain classes of failures, are inflexible, and are hard to scalp up. We present a novel approach, SOCFAD, to failure detection and recovery in multi-agent settings. SOCFAD is inspired by Social Comparison Theory from social psychology and includes the following key novel concepts: (a) utilizing other agents in the environment as information sources for failure detection, (b) a detection and repair method for previously undetectable failures using abductive inference based on other agents' beliefs, and (c) a decision-theoretic approach to selecting the information acquisition medium. An analysis of SOCFAD is presented, showing that the new method is complementary to previous approaches in terms of classes of failures detected.

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Kaminka GA, Tambe M. Social comparison for failure detection and recovery. In Singh MP, Rao A, Wooldridge MJ, editors, Intelligent Agents IV: Agent Theories, Architectures, and Languages - 4th International Workshop, ATAL 1997, Proceedings. Springer Verlag. 1998. p. 127-141. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/bfb0026755

Social comparison for failure detection and recovery

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Bibliographical note

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