Content- and Context-Related Trust in Open Multi-agent Systems Using Linked Data

摘要

In open multi-agent systems, linked data enables agents to communicate with each other and to gather knowledge for autonomous decision. Until now, trust is a factor for starting communications and ignores doubts about the content or context of ongoing communications. Several approaches are used to identify whom to trust and how human trust can be computationally modeled. Yet, they do not consider a change of context or of other agents' behavior at runtime. The proposed doctoral work aims to support content- and context-related trust in open multi-agent systems using linked data. Existing trust models need to be surveyed with respect to content- and context-related trust. A framework based on a fitting trust model and working with linked data must be developed to establish and dynamically refine trust relationships on the autonomous agents' point of view. This would enhance the applicability of decentralized systems without introducing central units as the history of the web demonstrates. Web engineers are hereby supported to work on a new level of abstraction using the decentralization, but not scrutinizing specific communication sequences.