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A probabilistic approach for maintaining trust based on evidence

Authors:

Chung-Wei Hang,

Munindar P. SinghAuthors Info & Claims

Journal of Artificial Intelligence Research, Volume 40, Issue 1

Pages 221 - 267

Published: 01 January 2011 Publication History

Abstract

Leading agent-based trust models address two important needs. First, they show how an agent may estimate the trustworthiness of another agent based on prior interactions. Second, they show how agents may share their knowledge in order to cooperatively assess the trustworthiness of others. However, in real-life settings, information relevant to trust is usually obtained piecemeal, not all at once. Unfortunately, the problem of maintaining trust has drawn little attention. Existing approaches handle trust updates in a heuristic, not a principled, manner.

This paper builds on a formal model that considers probability and certainty as two dimensions of trust. It proposes a mechanism using which an agent can update the amount of trust it places in other agents on an ongoing basis. This paper shows via simulation that the proposed approach (a) provides accurate estimates of the trustworthiness of agents that change behavior frequently; and (b) captures the dynamic behavior of the agents. This paper includes an evaluation based on a real dataset drawn from Amazon Marketplace, a leading e-commerce site.

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Cited By

Liu GYang QWang HLiu A(2021)Trust Assessment in Online Social NetworksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2019.291636618:2(994-1007)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1109/TDSC.2019.2916366
Bahri LCarminati BFerrari EBianco A(2018)Enhanced Audit Strategies for Collaborative and Accountable Data Sharing in Social NetworksACM Transactions on Internet Technology10.1145/313443918:4(1-19)Online publication date: 24-Apr-2018
https://dl.acm.org/doi/10.1145/3134439
Ruan YZhang PAlfantoukh LDurresi A(2017)Measurement Theory-Based Trust Management Framework for Online Social CommunitiesACM Transactions on Internet Technology10.1145/301577117:2(1-24)Online publication date: 24-Mar-2017
https://dl.acm.org/doi/10.1145/3015771
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A probabilistic approach for maintaining trust based on evidence
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence

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Published In

cover image Journal of Artificial Intelligence Research

Journal of Artificial Intelligence Research Volume 40, Issue 1

January 2011

831 pages

ISSN:1076-9757

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AI Access Foundation

El Segundo, CA, United States

Publication History

Published: 01 January 2011

Published in JAIR Volume 40, Issue 1

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Cited By

Liu GYang QWang HLiu A(2021)Trust Assessment in Online Social NetworksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2019.291636618:2(994-1007)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1109/TDSC.2019.2916366
Bahri LCarminati BFerrari EBianco A(2018)Enhanced Audit Strategies for Collaborative and Accountable Data Sharing in Social NetworksACM Transactions on Internet Technology10.1145/313443918:4(1-19)Online publication date: 24-Apr-2018
https://dl.acm.org/doi/10.1145/3134439
Ruan YZhang PAlfantoukh LDurresi A(2017)Measurement Theory-Based Trust Management Framework for Online Social CommunitiesACM Transactions on Internet Technology10.1145/301577117:2(1-24)Online publication date: 24-Mar-2017
https://dl.acm.org/doi/10.1145/3015771
Xu GZhang GXu CLiu BLi MRen YLi XFeng ZZhang D(2017)A multi-attribute rating based trust modelMultimedia Tools and Applications10.1007/s11042-015-2539-z76:4(5833-5849)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s11042-015-2539-z
Rishwaraj GPonnambalam SKiong L(2017)An efficient trust estimation model for multi-agent systems using temporal difference learningNeural Computing and Applications10.1007/s00521-016-2354-028:1(461-474)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s00521-016-2354-0
Ruan YDurresi A(2016)A survey of trust management systems for online social communities - Trust modeling, trust inference and attacksKnowledge-Based Systems10.1016/j.knosys.2016.05.042106:C(150-163)Online publication date: 15-Aug-2016
https://dl.acm.org/doi/10.1016/j.knosys.2016.05.042
Irissappane AZhang J(2015)A case-based reasoning framework to choose trust models for different E-marketplace environmentsJournal of Artificial Intelligence Research10.5555/2831407.283141852:1(477-505)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.5555/2831407.2831418
Muller TLiu YZhang JWeiss GYolum PBordini RElkind E(2015)The Fallacy of Endogenous Discounting of Trust RecommendationsProceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems10.5555/2772879.2772951(563-572)Online publication date: 4-May-2015
https://dl.acm.org/doi/10.5555/2772879.2772951
Hoelz BRalha C(2015)Towards a cognitive meta-model for adaptive trust and reputation in open multi-agent systemsAutonomous Agents and Multi-Agent Systems10.1007/s10458-014-9278-929:6(1125-1156)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1007/s10458-014-9278-9
Kalia AMurukannaiah PSingh M(2015)TRACE: A Dynamic Model of Trust for People-Driven Service EngagementsService-Oriented Computing10.1007/978-3-662-48616-0_24(353-361)Online publication date: 16-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-662-48616-0_24
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