Agent reasoning in large scale multi-agent systems requires techniques which often work with uncertainty and probability. In our research, we use trust and reputation principles to support agent reasoning and decisioning. Information about agents past behaviour and their qualities are transformed to multi-context trust. It allows to view a single agent from different point of views, because agents are judged in different aspects — contexts. In this paper we describe event driven multi-context trust model as extension of Hierarchical Model of Trust in Contexts (HMTC), when different types of events causes trust updates. This extension of HMTC also provides some solutions for avoiding conflicts which may appear in previous HMTC.
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