Building a fuzzy trust network in unsupervised multi-agent environments

In automated and unsupervised multi-agent environments, where agents act on behalf of their stakeholders, the measurement and computation of trust is a key building block upon which all business interaction scenarios rely. In environments, where the individual and independent calculation of trustwo...

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Main Authors: Chang, Elizabeth, Schmidt, S., Steele, R., Dillon, Tharam S.
Format: Conference Paper
Published: Springer-Verlag 2005
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/22908
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author Chang, Elizabeth
Schmidt, S.
Steele, R.
Dillon, Tharam S.
author_facet Chang, Elizabeth
Schmidt, S.
Steele, R.
Dillon, Tharam S.
author_sort Chang, Elizabeth
building Curtin Institutional Repository
collection Online Access
description In automated and unsupervised multi-agent environments, where agents act on behalf of their stakeholders, the measurement and computation of trust is a key building block upon which all business interaction scenarios rely. In environments, where the individual and independent calculation of trustworthiness values for future negotiation partners is desired, flexible algorithms and models imitating human reasoning are crucial. This paper introduces a trust evaluation model that imitates human reasoning by using fuzzy logic concepts. Furthermore, post-interaction processes such as business interaction reviews and credibility adjustment are used to continuously build and refine an information repository for future trust evaluation processes. Fuzzy logic offers a mathematical approach encompassing uncertainty and tolerance of imprecise data, and combined with our highly customizable model, it allows to meet the security needs of different stakeholders.
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format Conference Paper
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institution Curtin University Malaysia
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publishDate 2005
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spelling curtin-20.500.11937-229082018-10-02T05:43:36Z Building a fuzzy trust network in unsupervised multi-agent environments Chang, Elizabeth Schmidt, S. Steele, R. Dillon, Tharam S. fuzzy logic multi-agent fuzzy trust network trust information systems security unsupervised multi-agent environment In automated and unsupervised multi-agent environments, where agents act on behalf of their stakeholders, the measurement and computation of trust is a key building block upon which all business interaction scenarios rely. In environments, where the individual and independent calculation of trustworthiness values for future negotiation partners is desired, flexible algorithms and models imitating human reasoning are crucial. This paper introduces a trust evaluation model that imitates human reasoning by using fuzzy logic concepts. Furthermore, post-interaction processes such as business interaction reviews and credibility adjustment are used to continuously build and refine an information repository for future trust evaluation processes. Fuzzy logic offers a mathematical approach encompassing uncertainty and tolerance of imprecise data, and combined with our highly customizable model, it allows to meet the security needs of different stakeholders. 2005 Conference Paper http://hdl.handle.net/20.500.11937/22908 10.1007/11575863_103 Springer-Verlag restricted
spellingShingle fuzzy logic
multi-agent
fuzzy trust network
trust
information systems
security
unsupervised multi-agent environment
Chang, Elizabeth
Schmidt, S.
Steele, R.
Dillon, Tharam S.
Building a fuzzy trust network in unsupervised multi-agent environments
title Building a fuzzy trust network in unsupervised multi-agent environments
title_full Building a fuzzy trust network in unsupervised multi-agent environments
title_fullStr Building a fuzzy trust network in unsupervised multi-agent environments
title_full_unstemmed Building a fuzzy trust network in unsupervised multi-agent environments
title_short Building a fuzzy trust network in unsupervised multi-agent environments
title_sort building a fuzzy trust network in unsupervised multi-agent environments
topic fuzzy logic
multi-agent
fuzzy trust network
trust
information systems
security
unsupervised multi-agent environment
url http://hdl.handle.net/20.500.11937/22908