Certified Reputation - How an Agent Can Trust a Stranger
Huynh, T.D., Jennings, N. R. and Shadbolt, N.R. (2006) Certified Reputation - How an Agent Can Trust a Stranger. In, The Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, 08 - 12 May 2006. , 1217-1224.
Current computational trust models are usually built either on an agent's direct experience of an interaction partner (interaction trust) or reports provided by third parties about their experiences with a partner (witness reputation). However, both of these approaches have their limitations. Models using direct experience often result in poor performance until an agent has had a su±cient number of interactions to build up a reliable picture of a particular partner and witness reports rely on self-interested agents being willing to freely share their experience. To this end, this paper presents Certified Reputation (CR), a novel model of trust that can overcome these limitations. Specifically, CR works by allowing agents to actively provide third-party references about their previous performance as a means of building up the trust in them of their potential interaction partners. By so doing, trust relationships can quickly be established with very little cost to the involved parties. Here we empirically evaluate CR and show that it helps agents pick better interaction partners more quickly than models that do not incorporate this form of trust.
|Item Type:||Conference or Workshop Item (Paper)|
|Keywords:||Trust, Reputation, Multi-Agent Systems|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Web & Internet Science
|Date Deposited:||16 May 2006|
|Last Modified:||03 Dec 2014 10:55|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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