Decentralised Task Allocation in Multi-Agent Systems under Uncertainty

Design next-generation AI for coordinating intelligent systems under uncertainty. This PhD tackles a core challenge in multi-agent systems: how autonomous agents coordinate task allocation under limited information. You will develop novel algorithms combining game theory, optimisation, and machine learning, with applications in real-world large-scale systems.

How can multiple intelligent agents coordinate decisions efficiently in complex, uncertain environments without central control? This PhD addresses a fundamental challenge in artificial intelligence and multi-agent systems: decentralised task allocation under limited information and competing objectives.

In many real-world systems, from logistics networks to distributed services, decision-making is inherently decentralised. Agents must act based on partial, local information while interacting with others who may have different goals. While cooperative coordination is well understood, much less is known about how to design efficient and robust coordination mechanisms in settings that involve uncertainty, delays, and heterogeneous behaviour.

This project will develop new algorithmic and theoretical foundations for decentralised coordination in such environments. The core focus is on designing mechanisms that enable agents to allocate tasks efficiently while maintaining robustness to uncertainty and dynamic conditions.

As a PhD student, you will:

• Develop mathematical models for multi-agent decision-making under partial observability
• Design decentralised coordination mechanisms using ideas from optimisation and game theory
• Explore learning-based approaches, including multi-agent reinforcement learning, to enable adaptive behaviour
• Build simulation environments to evaluate system performance under realistic conditions
• Analyse robustness under uncertainty, delays, and abnormal agent behaviour, and design mechanisms that maintain stable performance

The project combines tools from game theory, machine learning, optimisation, and probabilistic planning. You will work at the intersection of these areas to develop scalable, principled solutions to complex coordination problems.

A key strength of this PhD is its unique combination of rigorous theory and real-world impact. Aurrigo International Plc, the industrial partner for this project, will provide direct access to large-scale coordination challenges in practice. You will work closely with academic supervisors and collaborate with Aurrigo’s engineering teams, gaining valuable industry insight throughout the project. A dedicated four-month industrial placement will offer hands-on experience, enabling you to test and refine your ideas in realistic settings while developing strong industry and entrepreneurial skills. This integration ensures your research delivers both methodological depth and practical relevance, preparing you for careers in academia and advanced AI development.

You will join a strong research environment in artificial intelligence and multi-agent systems, with opportunities to collaborate across academia and industry. The project offers the chance to publish in leading venues and to contribute to cutting-edge developments in decentralised AI.

This PhD is particularly suited to candidates with a strong background in computer science, mathematics, or a related field, and an interest in areas such as multi-agent systems, machine learning, optimisation, or game theory.

By the end of the project, you will have developed expertise in designing and analysing complex multi-agent systems, with skills applicable to a wide range of domains including logistics, distributed systems, and intelligent infrastructure.

This project covers all tuition fees and includes an annual stipend of £21,805.

Please note that the successful candidate will be responsible for any costs relating to moving to Birmingham and/or visiting the Aston campus. International students must meet the financial requirements for the visa, flights, and NHS Surcharge. Applicants should be confident that they can meet these costs before applying. 

Further information can be found here: Financial Requirements | Aston University

Applicants should have been awarded, or expect to achieve, a Masters degree in a relevant subject with a 60% or higher weighted average, and/or a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution).

Desirable / Essential Skills or Experience 

We are looking for highly motivated candidates with a strong background in computer science, mathematics, or a related field.

Essential:

• Strong analytical and problem-solving skills
• Solid programming experience (e.g. Python or similar)
• Good understanding of algorithms, probability, and mathematical modelling
• Good understanding of artificial intelligence and machine learning fundamentals
• Ability to work independently and communicate research ideas clearly

Desirable:

• Background in one or more of the following: multi-agent systems, optimisation, or game theory
• Experience with reinforcement learning or probabilistic modelling
• Familiarity with simulation-based experimentation or large-scale system modelling
• Interest in both theoretical research and real-world applications

We can only consider applications that are complete and have all supporting documents. Applications that do not provide all the relevant documents will be automatically rejected. Your application must include: 

1.  English language copies of the transcripts and certificates for all your higher education degrees, including any Bachelor degrees.
2. A Research Statement detailing your understanding of the research area, how you would approach the project, and a brief review of relevant literature. Be sure to use the title of the research project you are applying for. There is no set format or word count. 
3. A personal statement which outlines any further information which you think is relevant to your application, such as your personal suitability for research, career aspirations, possible future research interests, and further description of relevant employment experience. 
4. A Curriculum Vitae (Resume) which details your education and work history. 
5. Two academic referees who can discuss your suitability for independent research. References must be on headed paper, signed and dated no more than 2 years old. At least one reference should be from your most recent University. You can submit your references at a later date if necessary. 
6. Evidence that you meet the English Language requirements. If you do not currently meet the language requirements, you can submit this at a later stage. 
7. A copy of your passport. Where relevant, include evidence of settled or pre-settled status.

If you require further information about the application process, please contact the Postgraduate Admissions team at pgr_admissions@aston.ac.uk.

International Applicants 

International applicants are welcome to apply for this position. 

Studying a PhD is great route into academia and industries that are centred on research and innovation. Areas with a demand for very high level and specialised research skills often demand PhDs.

In addition to this specialist knowledge, PhD education will help you to develop a set of valuable transferrable skills. The very nature of studying an intensive research degree will enable you to become a team player, develop problem-solving skills, analytical thinking, and advanced presentation and communication skills.

The variety of PhD project topics at Aston means that the destinations of our graduates vary substantially. Some choose to continue into academia, at either Aston or other leading institutions, while others go onto use their newly acquired skills in a range of research, healthcare, industry or charitable fields. When selecting your chosen PhD path at Aston, your supervisor will be able to provide you with relevant career opportunities that could be available to you in your specialist area.