Qualification: Modelling Trust in Artificial Agents, A First Step Toward the Analysis of e-Trust
Taddeo describes one-shot interaction as very common in distributed artificial-agent systems and argues that an agent's trustworthiness can be assessed from its past performance without repeated interaction with the same counterpart. This independently qualifies Kaal's stronger formulation: the source supports the prevalence of one-shot agent encounters and the need for portable performance history, but it does not establish that every agent interaction is one-shot or that one-shot interaction is literally universal by default.
Affirmed commentary position. This record extends a source-bound scholarly claim but is not a verbatim paper claim.
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Topics
ai-and-agentsrisk-and-incentivesscholarly-growth-coveragescholarly-literaturetrust-and-reputationmulti-agent-systems
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