Driving Sustainability: Myopic Mean Field Games and MARL for Incentive Mechanisms in Manufacturing Supply Chains PhD

Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical systems (eCPS). The focus in this research is on analysing and managing agent behaviour for enhanced sustainability and resilience. The student will be presented with a chance to shape actionable solutions for global industries, all while collaborating with experts in the prestigious International Systems Realisation Partnership. Furthermore, the student will gain invaluable skills in data analysis, problem-solving, teamwork, and communication—setting the stage for a thriving career in research and innovation.

This project is situated within the evolving field of cyber-physical systems (eCPS), which has significant relevance in today's technological landscape. As industries continue to integrate digital and physical systems, the role of eCPS in enhancing automation, control, and sustainability becomes increasingly important.

The aim of the project is to explore the collaborative dynamics of agents within eCPS, with a specific focus on aligning their behaviours towards achieving sustainability goals. Cranfield University provides an ideal setting for this research, offering a wealth of resources and expertise in engineering and digital technologies.

The expected outcome of the project is the development of novel analytical frameworks grounded in Mean Field Game (MFG) theory and Multi-Agent Reinforcement Learning (MARL), which are tailored for eCPS. These frameworks will facilitate the creation of effective control strategies that can improve sustainability and resilience in decentralised manufacturing networks.

A unique selling point of this project is the opportunity for collaboration with world-leading experts through the International Systems Realisation Partnership, as well as potential exposure to travel, conferences, and external training opportunities.

The student working on this project will gain a diverse set of transferable skills in areas such as system design, AI integration, cyber-physical systems, and sustainability, which will enhance their employability and prepare them for a successful career in both academia and industry.

At a glance

Application deadline06 Aug 2025
Award type(s)PhD
Start date29 Sep 2025
Duration of award3 years
EligibilityUK, EU, Rest of world
Reference numberSATM542

Entry requirements

Applicants should have a first or second class UK honours degree or equivalent in in Design, Engineering, Computer Science/IT or a related subject. Experience in system design, and/or manufacturing is preferred, and digital technologies is required. It welcomes applications from individuals passionate about addressing real-world challenges, in an inclusive and collaborative research environment.

Funding

This studentship is open to both UK and International applications. This is a self funded PhD opportunity.

Find out more about tuition fees.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.