Algorithmic Evaluation of Trust in Multilevel Model

Artificial agents are autonomous entities that should behave rationally by their own control. They should have also some social abilities that enable them to make strategic decision inside a multi-agent community. One of such decision is to select proper partner which it believes that its behaviour will be reliable and trustworthy. We address area of trust which may be important for improving agent's reasoning capabilities and by this also rationality of its behaviour within an agent or multi-agent system. This paper introduces specification of the model which is used for representation of trusts and their hierarchy in agent's beliefs. In fact this is a part of agents's belief base and it is used when decision about some system element trustworthy takes part in agent's reasoning process. For these purposes, we develop Hierarchical Model of Trust in Context which is represented by multilevel graph, where each node of the graph represents different aspects (contexts) of trustee and each edge of the graph represents correlation between different aspects. This is useful to modelling trust in respect to context-aware environment.