A Fuzzy-Logical Approach for Integrating Multi-agent Estimations

Roland M. Müller

A Fuzzy-Logical Approach for Integrating Multi-agent Estimations

Roland M. Müller

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

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Abstract

This paper proposes a novel approach for integrating estimations from multiple agents. The approach is based on the fuzzy set theory. However, compared to existing fuzzy logical methods that use fuzzy if-then rules, this method is based on solving an over-determined fuzzy equation system. The result is either a global inconsistency message or the consistent core of the equation system. We demonstrate the approach with data from an actual case study undertaken by a German automotive manufacturer.

Original language	English
Title of host publication	Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009
Subtitle of host publication	San Francisco, California, USA, August 6-9, 2009
Publisher	Association for Information Systems
Number of pages	12
Publication status	Published - 6 Aug 2009
Event	15th Americas Conference on Information Systems, AMCIS 2009 - San Francisco, United States Duration: 6 Aug 2011 → 9 Aug 2011 Conference number: 15

Conference

Conference	15th Americas Conference on Information Systems, AMCIS 2009
Abbreviated title	AMCIS
Country/Territory	United States
City	San Francisco
Period	6/08/11 → 9/08/11

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https://aisel.aisnet.org/amcis2009/323/

Cite this

@inproceedings{109edb25ec4b488fb7937ca9ce5172f0,

title = "A Fuzzy-Logical Approach for Integrating Multi-agent Estimations",

abstract = "This paper proposes a novel approach for integrating estimations from multiple agents. The approach is based on the fuzzy set theory. However, compared to existing fuzzy logical methods that use fuzzy if-then rules, this method is based on solving an over-determined fuzzy equation system. The result is either a global inconsistency message or the consistent core of the equation system. We demonstrate the approach with data from an actual case study undertaken by a German automotive manufacturer.",

author = "M{\"u}ller, \{Roland M.\}",

year = "2009",

month = aug,

day = "6",

language = "English",

booktitle = "Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009",

publisher = "Association for Information Systems",

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note = "15th Americas Conference on Information Systems, AMCIS 2009, AMCIS ; Conference date: 06-08-2011 Through 09-08-2011",

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Müller, RM 2009, A Fuzzy-Logical Approach for Integrating Multi-agent Estimations. in Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009: San Francisco, California, USA, August 6-9, 2009., 323, Association for Information Systems, 15th Americas Conference on Information Systems, AMCIS 2009, San Francisco, California, United States, 6/08/11. <https://aisel.aisnet.org/amcis2009/323/>

A Fuzzy-Logical Approach for Integrating Multi-agent Estimations. / Müller, Roland M.
Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009: San Francisco, California, USA, August 6-9, 2009. Association for Information Systems, 2009. 323.

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

TY - GEN

T1 - A Fuzzy-Logical Approach for Integrating Multi-agent Estimations

AU - Müller, Roland M.

N1 - Conference code: 15

PY - 2009/8/6

Y1 - 2009/8/6

N2 - This paper proposes a novel approach for integrating estimations from multiple agents. The approach is based on the fuzzy set theory. However, compared to existing fuzzy logical methods that use fuzzy if-then rules, this method is based on solving an over-determined fuzzy equation system. The result is either a global inconsistency message or the consistent core of the equation system. We demonstrate the approach with data from an actual case study undertaken by a German automotive manufacturer.

AB - This paper proposes a novel approach for integrating estimations from multiple agents. The approach is based on the fuzzy set theory. However, compared to existing fuzzy logical methods that use fuzzy if-then rules, this method is based on solving an over-determined fuzzy equation system. The result is either a global inconsistency message or the consistent core of the equation system. We demonstrate the approach with data from an actual case study undertaken by a German automotive manufacturer.

M3 - Conference contribution

BT - Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009

PB - Association for Information Systems

T2 - 15th Americas Conference on Information Systems, AMCIS 2009

Y2 - 6 August 2011 through 9 August 2011

ER -

A Fuzzy-Logical Approach for Integrating Multi-agent Estimations

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