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Stereotype reputation with limited observability
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Taylor, Phillip M., Griffiths, Nathan, Barakat, Lina and Miles, Simon (2017) Stereotype reputation with limited observability. In: AAMAS: International Conference on Autonomous Agents and Multiagent Systems, São Paulo, Brazil, 8-12 May 2017. Published in: Lecture Notes in Artificial Intelligence [LNCS], 10642 pp. 84-102. ISBN 9783319716817. doi:10.1007/978-3-319-71682-4 ISSN 1611-3349.
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Official URL: https://doi.org/10.1007/978-3-319-71682-4
Abstract
Assessing trust and reputation is essential in multi-agent systems where agents must decide who to interact with. Assessment typically relies on the direct experience of a trustor with a trustee agent, or on information from witnesses. Where direct or witness information is unavailable, such as when agent turnover is high, stereotypes learned from common traits and behaviour can provide this information. Such traits may be only partially or subjectively observed, with witnesses not observing traits of some trustees or interpreting their observations differently. Existing stereotype-based techniques are unable to account for such partial observability and subjectivity. In this paper we propose a method for extracting information from witness observations that enables stereotypes to be applied in partially and subjectively observable dynamic environments. Specifically, we present a mechanism for learning translations between observations made by trustor and witness agents with subjective interpretations of traits. We show through simulations that such translation is necessary for reliable reputation assessments in dynamic environments with partial and subjective observability.
| Item Type: | Conference Item (Paper) | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Journal or Publication Title: | Lecture Notes in Artificial Intelligence [LNCS] | ||||||
| Publisher: | Springer International Publishing | ||||||
| Place of Publication: | Cham | ||||||
| ISBN: | 9783319716817 | ||||||
| ISSN: | 1611-3349 | ||||||
| Book Title: | Autonomous Agents and Multiagent Systems. AAMAS 2017 | ||||||
| Editor: | SukthankarJuan, Gita and Rodriguez-Aguilar, A. | ||||||
| Official Date: | 25 November 2017 | ||||||
| Dates: |
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| Volume: | 10642 | ||||||
| Page Range: | pp. 84-102 | ||||||
| DOI: | 10.1007/978-3-319-71682-4 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 10 January 2018 | ||||||
| Date of first compliant Open Access: | 1 May 2018 | ||||||
| Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||||
| Grant number: | EP/M012662/1 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | AAMAS: International Conference on Autonomous Agents and Multiagent Systems | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | São Paulo, Brazil | ||||||
| Date(s) of Event: | 8-12 May 2017 |
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