Context model for multi-agent system reconfiguration

Krzysztof Stebel; Dariusz Choiński

doi:10.1007/978-3-540-85776-1_1

Context model for multi-agent system reconfiguration

Department of Automatic Control and Robotics (RAU/RAU3)

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

2 Citations (Scopus)

Abstract

This paper presents a reconfigurable multi-agent system (MAS) applied to distributed control system (DCS). Agents co-operate, evaluating the system on different levels of information abstraction. Context-based statistical remote expert agent or local supervisory agent are used to evaluate control agent performance. Using expert-selected period of good performance the reference distribution function is proposed. Periodically, for any monitoring period, a sample of observations is taken for local or remote system performance monitoring. Because evaluation may also be carried out remotely two cases should be considered. Remote expert observes changes of parameters that come from process performance degradation. Second case refers to communication problems when data transmission is corrupted and can not be used for system evaluation. Because of that application, context model is necessary to inform the remote expert about transmission quality. For evaluation of transmission channel, the idea of a context tree is utilised. Number of nodes and leaves taken into considerations depends on the expert's knowledge.

Original language	English
Title of host publication	Artificial Intelligence
Subtitle of host publication	Methodology, Systems, and Applications - 13th International Conference, AIMSA 2008, Proceedings
Pages	1-11
Number of pages	11
DOIs	https://doi.org/10.1007/978-3-540-85776-1_1
Publication status	Published - 2008
Event	13th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2008 - Varna, Bulgaria Duration: 4 Sept 2008 → 6 Sept 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5253 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2008
Country/Territory	Bulgaria
City	Varna
Period	4/09/08 → 6/09/08

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Context model
Kullback-Leibler divergence
Multi-agent system
System reconfiguration

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-85776-1_1

Cite this

Stebel, K., & Choiński, D. (2008). Context model for multi-agent system reconfiguration. In Artificial Intelligence: Methodology, Systems, and Applications - 13th International Conference, AIMSA 2008, Proceedings (pp. 1-11). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5253 LNAI). https://doi.org/10.1007/978-3-540-85776-1_1

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Stebel, K & Choiński, D 2008, Context model for multi-agent system reconfiguration. in Artificial Intelligence: Methodology, Systems, and Applications - 13th International Conference, AIMSA 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5253 LNAI, pp. 1-11, 13th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2008, Varna, Bulgaria, 4/09/08. https://doi.org/10.1007/978-3-540-85776-1_1

Context model for multi-agent system reconfiguration. / Stebel, Krzysztof ; Choiński, Dariusz.
Artificial Intelligence: Methodology, Systems, and Applications - 13th International Conference, AIMSA 2008, Proceedings. 2008. p. 1-11 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5253 LNAI).

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

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AB - This paper presents a reconfigurable multi-agent system (MAS) applied to distributed control system (DCS). Agents co-operate, evaluating the system on different levels of information abstraction. Context-based statistical remote expert agent or local supervisory agent are used to evaluate control agent performance. Using expert-selected period of good performance the reference distribution function is proposed. Periodically, for any monitoring period, a sample of observations is taken for local or remote system performance monitoring. Because evaluation may also be carried out remotely two cases should be considered. Remote expert observes changes of parameters that come from process performance degradation. Second case refers to communication problems when data transmission is corrupted and can not be used for system evaluation. Because of that application, context model is necessary to inform the remote expert about transmission quality. For evaluation of transmission channel, the idea of a context tree is utilised. Number of nodes and leaves taken into considerations depends on the expert's knowledge.

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KW - System reconfiguration

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M3 - Conference contribution

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SN - 9783540857754

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Stebel K , Choiński D. Context model for multi-agent system reconfiguration. In Artificial Intelligence: Methodology, Systems, and Applications - 13th International Conference, AIMSA 2008, Proceedings. 2008. p. 1-11. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-85776-1_1

Context model for multi-agent system reconfiguration

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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