Evaluating trustworthiness from past performances: Interval-based approaches

Ben-Naim, J; Prade, H

Evaluating trustworthiness from past performances: Interval-based approaches

Ben-Naim, J Prade, H

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, 5291 LNAI pp. 33 - 46
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Ben-Naim, J	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, 5291 LNAI pp. 33 - 46	en_US
dc.identifier.isbn	3540879927	en_US
dc.identifier.isbn	9783540879923	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33008
dc.description.abstract	In many multi-agent systems, the user has to decide whether he (or she) sufficiently trusts a certain agent to achieve a certain goal. To help users to make such decisions, an increasing number of trust systems have been developed. By trust system, we mean a system that gathers information about an agent and evaluates its trustworthiness from this information. The aim of the present paper is to develop new trust systems that overcome limitations of existing ones. This is a challenging problem that raises questions such as: how trustworthiness may be represented, and from which information it may be estimated? We assume that a set of grades describing the past performances of the agent is given. With this common basis, two approaches are proposed. In the first one, the aim is to construct an interval that summarizes the grades. Such an interval gives a good account of the trustworthiness of the agent. We establish axioms that should be satisfied by summarizing methods, devise a particular method based on pulling, and check that it satisfies the axioms, which provides theoretical justifications for it. In the second approach, which is more briefly presented, a level of trust as the certainty that a future grade will be good, and a level of distrust as the fear that a future grade may be bad, are computed on the basis of the past grades. This approach is based on possibility theory and provides, thanks to the two levels, another view of trustworthiness, as well as summarizing intervals. © 2008 Springer-Verlag.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-540-87993-0_5	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Evaluating trustworthiness from past performances: Interval-based approaches	en_US
dc.type	Conference Proceeding
utslib.citation.volume	5291 LNAI	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	5291 LNAI	en_US

Abstract:

In many multi-agent systems, the user has to decide whether he (or she) sufficiently trusts a certain agent to achieve a certain goal. To help users to make such decisions, an increasing number of trust systems have been developed. By trust system, we mean a system that gathers information about an agent and evaluates its trustworthiness from this information. The aim of the present paper is to develop new trust systems that overcome limitations of existing ones. This is a challenging problem that raises questions such as: how trustworthiness may be represented, and from which information it may be estimated? We assume that a set of grades describing the past performances of the agent is given. With this common basis, two approaches are proposed. In the first one, the aim is to construct an interval that summarizes the grades. Such an interval gives a good account of the trustworthiness of the agent. We establish axioms that should be satisfied by summarizing methods, devise a particular method based on pulling, and check that it satisfies the axioms, which provides theoretical justifications for it. In the second approach, which is more briefly presented, a level of trust as the certainty that a future grade will be good, and a level of distrust as the fear that a future grade may be bad, are computed on the basis of the past grades. This approach is based on possibility theory and provides, thanks to the two levels, another view of trustworthiness, as well as summarizing intervals. © 2008 Springer-Verlag.

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http://hdl.handle.net/10453/33008