Abstract

Trust has been the focus of many research projects, both theoretical and practical, in
the recent years, particularly in domains where open multi-agent technologies are applied
(e.g., Internet-based markets, Information retrieval, etc.). The importance of trust in such
domains arises mainly because it provides a social control that regulates the relationships
and interactions among agents. Despite the growing number of various multi-agent applications, they still encounter many challenges in their formal modeling and the verification
of agents’ behaviors. Many formalisms and approaches that facilitate the specifications of
trust in Multi-Agent Systems (MASs) can be found in the literature. However, most of these
approaches focus on the cognitive side of trust where the trusting entity is normally capable
of exhibiting properties about beliefs, desires, and intentions. Hence, the trust is considered
as a belief of an agent (the truster) involving ability and willingness of the trustee to perform some actions for the truster. Nevertheless, in open MASs, entities can join and leave
the interactions at any time. This means MASs will actually provide no guarantee about the
behavior of their agents, which makes the capability of reasoning about trust and checking
the existence of untrusted computations highly desired.
This thesis aims to address the problem of modeling and verifying at design time
trust in MASs by (1) considering a cognitive-independent view of trust where trust ingredients are seen from a non-epistemic angle, (2) introducing a logical language named Trust
Computation Tree Logic (TCTL), which extends CTL with preconditional, conditional, and graded trust operators along with a set of reasoning postulates in order to explore its capabilities, (3) proposing a new accessibility relation which is needed to define the semantics
of the trust modal operators. This accessibility relation is defined so that it captures the
intuition of trust while being easily computable, (4) investigating the most intuitive and
efficient algorithm for computing the trust set by developing, implementing, and experimenting different model checking techniques in order to compare between them in terms of
memory consumption, efficiency, and scalability with regard to the number of considered
agents, (5) evaluating the performance of the model checking techniques by analyzing the
time and space complexity.
The approach has been applied to different application domains to evaluate its computational performance and scalability. The obtained results reveal the effectiveness of the
proposed approach, making it a promising methodology in practice.