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Thesis defences

PhD Oral Exam - Narges Baharloo, Information Systems Engineering

Model Checking the Interplay of Trust and Commitments in Multi-Agent Systems and Applications

Date & time
Tuesday, April 30, 2024
1 p.m. – 4 p.m.

This event is free


School of Graduate Studies


Nadeem Butt



When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.


Effective and secure communication among agents is crucial for developing open multi-agent systems (MASs). In such systems, agents operate autonomously and engage in interactions within unpredictable and dynamic environments, making it essential to contemplate security-driven, social and communicative modalities. The concepts of trust and social commitments have garnered considerable attention within MASs to model flexible and secure communication mechanisms. Numerous attempts have been made to define their semantics separately. Nevertheless, there is still a need for more in-depth exploration of the connection between trust and social commitments.

On the other hand, the combination of IoT and ad hoc networks has introduced novel service models in various multi-agent applications. However, effective communication remains the essential factor in enabling the coordination and interaction among various components within these systems. This cooperation empowers them to work together to address challenges that may exceed the capabilities of individual intelligent elements. One primary concern faced by applications based on IoT-ad hoc networks applications is ensuring the reliability of their components, especially when dealing with entities that may engage in malicious behavior and uncertainty.

Moreover, in many situations, trust falls along a continuum, with various levels of strength and weakness. The level of trust often depends on factors such as past experiences, evidence of reliability, transparency, and communication. Critical infrastructure systems, like banking and healthcare, rely on strong trust in data security and privacy. Systems with strong trust are often entrusted with significant responsibilities and critical tasks.

This thesis addresses these challenges through three main verification approaches: 1) model checking combined trust and commitments framework; 2) verifying three-valued trust model for IoT-ad hoc Systems; and 3) model checking weak and strong trust over commitments in MASs. In the first approach, we develop a formal and practical framework, TCTLC, for handling trust over social commitments. We extend the Model Checker for Multi-Agent Systems (MCMAS) with the MCMAS-TC tool and analyse its time and space complexity. We also validate the technique through an industrial case study. In the second approach, we propose a 3v trust model using three-valued logic to address trust over social commitments in uncertain IoT-ad hoc settings. We introduce the 3v-TCTLC modeling language to handle uncertainty in trust assessments. Moreover, we enhance the "MACMAS-interactor" tool to enable its interaction with the MCMAS-TC model checker by incorporating new functionalities to handle our 3v-TCTLC logic. This approach is validated through case studies in smart health monitoring and smart home systems, verifying system models against specified criteria in uncertain contexts. The third approach introduces a novel logic, T^{ws} CTLC, designed to capture properties related to both weak and strong trust over commitments. We establish the semantics over the extended interpretation of the original multi-agent systems formalism and provide postulates with accompanying proofs to support our logic. The approach is validated using a scalable case study.

These contributions aim to advance trust and commitment management in MASs and enhance the reliability and effectiveness of IoT in smart environments, providing practical tools and methodologies for uncertain scenarios.

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