Quantitative Verification of Supply Chain Models in the Agri-Food Efficiency Systems: Ensuring Efficiency, Fairness, and Sustainability

About the project

About the Project This project will develop a formal verification framework to address sustainability challenges in complex multi-agent systems (MASs). These systems capture interactions between autonomous agents—individuals, organisations, or digital entities—whose decisions involve uncertainty, incentives, and trade-offs. While central to modern socio-technical systems, existing tools lack the ability to provide rigorous guarantees on whether sustainable and fair outcomes can be achieved. This research will integrate formal verification with game-theoretic reasoning to evaluate critical properties such as fairness, efficiency, resilience, and environmental impact. The framework will be applied to agri-food supply chains [1,2], which are important to global food security but face pressing challenges around waste, emissions, and fairness. By modelling stakeholders as interacting agents, the project will identify conditions under which sustainable and equitable strategies exist and assess their resilience to disruptions. Practical case studies, such as organic food supply chains, will provide real-world validation, focusing on risks including waste, inefficiency, and lack of transparency. Building on Alternating-time Temporal Logic [3] and preliminary work on quantitative verification of information transparency [4,6] and strategic reasoning about responsibility [5], this PhD will apply these methods to tackle sustainability, fairness, and resilience in multi-agent systems. The student will gain expertise in temporal logics, probabilistic verification, and game-theoretic reasoning, as well as interdisciplinary training in sustainability science and risk assessment. They will also gain hands-on experience with verification tools and their application to realistic case studies, preparing them for cross-sector careers at the intersection of computing, trustworthy AI, and sustainable agri-food systems. Requirements: Skills required: Degree in computer science, mathematics, or related fields; Strong computer science and/or mathematical background (with particular attention on formal methods and logic); Good programming skills. Please note that this project is not open to researchers from Afghanistan, Cameroon, Myanmar, Sudan or Iran. Supervisors: Chunyan Mu ( chunyan.mu@abdn.ac.uk ) Brian Logan ( Brian.logan@abdn.ac.uk ) Adewale Adenuga ( a.adenuga@qub.ac.uk ) Enquiries: Chunyan Mu ( chunyan.mu@abdn.ac.uk ) Application Deadline: 12:00 noon (UK time) Friday, 16 October 2026

Research areas