Reputation-based Provider Incentivisation for Provenance Provision

Lina Barakat; Samhar Mahmoud; Phillip Taylor; Nathan Griffiths; Simon Miles

Reputation-based Provider Incentivisation for Provenance Provision

Lina Barakat, Samhar Mahmoud, Phillip Taylor, Nathan Griffiths, Simon Miles

University of Warwick

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

2 Citations (Scopus)

71 Downloads (Pure)

Abstract

Knowledge of circumstances under which past service provisions have occurred enables clients to make more informed selection decisions regarding their future interaction partners. Service providers, however, may often be reluctant to release such circumstances due to the cost and effort required, or to protect their interests. In response, we introduce a reputation-based incentivisation framework, which motivates providers towards the desired behaviour of reporting circumstances via influencing two reputation-related factors: the weights of past provider interactions, which directly impact the provider's reputation estimate, and the overall confidence in such estimates.

Original language	English
Title of host publication	AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
Publisher	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages	1429-1430
Number of pages	2
ISBN (Electronic)	9781450342391
Publication status	Published - 2016
Event	15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore Duration: 9 May 2016 → 13 May 2016

Conference

Conference	15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/Territory	Singapore
City	Singapore
Period	9/05/2016 → 13/05/2016

Keywords

Circumstances
Incentivisation
Provenance
Reputation

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aamas2016_extendedabstractAccepted author manuscript, 269 KB

Cite this

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abstract = "Knowledge of circumstances under which past service provisions have occurred enables clients to make more informed selection decisions regarding their future interaction partners. Service providers, however, may often be reluctant to release such circumstances due to the cost and effort required, or to protect their interests. In response, we introduce a reputation-based incentivisation framework, which motivates providers towards the desired behaviour of reporting circumstances via influencing two reputation-related factors: the weights of past provider interactions, which directly impact the provider's reputation estimate, and the overall confidence in such estimates.",

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author = "Lina Barakat and Samhar Mahmoud and Phillip Taylor and Nathan Griffiths and Simon Miles",

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booktitle = "AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems",

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Barakat, L , Mahmoud, S, Taylor, P, Griffiths, N & Miles, S 2016, Reputation-based Provider Incentivisation for Provenance Provision. in AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1429-1430, 15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016, Singapore, Singapore, 9/05/2016.

Reputation-based Provider Incentivisation for Provenance Provision. / Barakat, Lina ; Mahmoud, Samhar; Taylor, Phillip et al.
AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2016. p. 1429-1430.

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

TY - CHAP

T1 - Reputation-based Provider Incentivisation for Provenance Provision

AU - Barakat, Lina

AU - Mahmoud, Samhar

AU - Taylor, Phillip

AU - Griffiths, Nathan

AU - Miles, Simon

PY - 2016

Y1 - 2016

N2 - Knowledge of circumstances under which past service provisions have occurred enables clients to make more informed selection decisions regarding their future interaction partners. Service providers, however, may often be reluctant to release such circumstances due to the cost and effort required, or to protect their interests. In response, we introduce a reputation-based incentivisation framework, which motivates providers towards the desired behaviour of reporting circumstances via influencing two reputation-related factors: the weights of past provider interactions, which directly impact the provider's reputation estimate, and the overall confidence in such estimates.

AB - Knowledge of circumstances under which past service provisions have occurred enables clients to make more informed selection decisions regarding their future interaction partners. Service providers, however, may often be reluctant to release such circumstances due to the cost and effort required, or to protect their interests. In response, we introduce a reputation-based incentivisation framework, which motivates providers towards the desired behaviour of reporting circumstances via influencing two reputation-related factors: the weights of past provider interactions, which directly impact the provider's reputation estimate, and the overall confidence in such estimates.

KW - Circumstances

KW - Incentivisation

KW - Provenance

KW - Reputation

UR - http://www.ifaamas.org/Proceedings/aamas2016/forms/authors2.htm#M

M3 - Conference paper

AN - SCOPUS:85014301024

SP - 1429

EP - 1430

BT - AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems

PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)

T2 - 15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016

Y2 - 9 May 2016 through 13 May 2016

ER -

Reputation-based Provider Incentivisation for Provenance Provision

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