Article

Developing trust in recommender agents

Authors:

Miquel Montaner,

Beatriz López,

Josep Lluís de la RosaAuthors Info & Claims

AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1

Pages 304 - 305

https://doi.org/10.1145/544741.544811

Published: 15 July 2002 Publication History

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Abstract

Trust is one of the most important social concepts that helps human agents to cope with their social environment and is present in all human interaction. Like in real world, agents should rely in some agents and mistrust in other ones to achieve a purpose. In this paper we develop a model of trust in the collaborative world as a new approach of recommender agents development. Mainly, we provide recommender agents with a technology to look for similar agents that advice him. The model presented comprehends the evolution of trust, that is, trust dynamics. Moreover, the model proposed emphasizes proactiveness since the agent looks for other agents in a lack for information situation instead of remaining passive or providing either a negative or empty answer to the user.

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Yang ZLin Z(2021)Interpretable video tag recommendation with multimedia deep learning frameworkInternet Research10.1108/INTR-08-2020-047132:2(518-535)Online publication date: 26-Jul-2021
https://doi.org/10.1108/INTR-08-2020-0471
Monteiro-Krebs LZaman BHtun NCaregnato SGeerts D(2021)Depicting Recommendations in Academia: How ResearchGate Communicates with Its Users (via Design or upon Request) About Recommender AlgorithmsData and Information in Online Environments10.1007/978-3-030-77417-2_1(3-25)Online publication date: 15-Jun-2021
https://doi.org/10.1007/978-3-030-77417-2_1
Binmad RLi M(2018)Psychology-Inspired Trust Restoration Framework in Distributed Multiagent SystemsScientific Programming10.1155/2018/75158602018Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1155/2018/7515860
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Developing trust in recommender agents

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Information

Published In

AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1

July 2002

540 pages

ISBN:1581134800

DOI:10.1145/544741

Conference Chairs:
Maria Gini
University of Minnesota, USA
,
Toru Ishida
Kyoto University, Japan
,
Program Chairs:
Cristiano Castelfranchi
CNR and Università di Siena, Italy
,
W. Lewis Johnson
University of Southern California, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2002

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AAMAS02

Sponsor:

AAMAS02: The First International Joint Conference on Autonomous Agents and Multi-Agent Systems ( formerly known as Autonomous Agents )

July 15 - 19, 2002

Bologna, Italy

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

View all

Yang ZLin Z(2021)Interpretable video tag recommendation with multimedia deep learning frameworkInternet Research10.1108/INTR-08-2020-047132:2(518-535)Online publication date: 26-Jul-2021
https://doi.org/10.1108/INTR-08-2020-0471
Monteiro-Krebs LZaman BHtun NCaregnato SGeerts D(2021)Depicting Recommendations in Academia: How ResearchGate Communicates with Its Users (via Design or upon Request) About Recommender AlgorithmsData and Information in Online Environments10.1007/978-3-030-77417-2_1(3-25)Online publication date: 15-Jun-2021
https://doi.org/10.1007/978-3-030-77417-2_1
Binmad RLi M(2018)Psychology-Inspired Trust Restoration Framework in Distributed Multiagent SystemsScientific Programming10.1155/2018/75158602018Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1155/2018/7515860
Tamargo LGottifredi SGarcía ASimari G(2017)Sharing beliefs among agents with different degrees of credibilityKnowledge and Information Systems10.1007/s10115-016-0964-650:3(999-1031)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s10115-016-0964-6
Gallege LRaje RTrien JProwell SGoodall JBridges R(2016)Towards Selecting and Recommending Online Software Services by Evaluating External AttributesProceedings of the 11th Annual Cyber and Information Security Research Conference10.1145/2897795.2897797(1-4)Online publication date: 5-Apr-2016
https://dl.acm.org/doi/10.1145/2897795.2897797
Hassan TShah PKhan F(2016)Fusion of motivational strategies with recommender system innovative framework for digital repositories2016 International Conference on Computing, Electronic and Electrical Engineering (ICE Cube)10.1109/ICECUBE.2016.7495249(32-36)Online publication date: Apr-2016
https://doi.org/10.1109/ICECUBE.2016.7495249
Granatyr JBotelho VLessing OScalabrin EBarthès JEnembreck F(2015)Trust and Reputation Models for Multiagent SystemsACM Computing Surveys10.1145/281682648:2(1-42)Online publication date: 12-Oct-2015
https://dl.acm.org/doi/10.1145/2816826
Chang WDiaz AHung P(2015)Estimating trust valueInformation Systems Frontiers10.1007/s10796-014-9519-017:6(1381-1400)Online publication date: 1-Dec-2015
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Pal S(2013)Cloud ComputingCloud Computing Service and Deployment Models10.4018/978-1-4666-2187-9.ch010(191-207)Online publication date: 2013
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Simulating rational social normative trust, predictive trust, and predictive reliance between agents

Developing artificial agents worthy of trust: "Would you buy a used car from this artificial agent?"

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