About the Project
Supervisor: Dr Vahid Yazdanpanah
This project will develop computational methods to detect responsibility gaps, attribute collective failures, and support safer oversight of multiagent systems under uncertainty and partial observability.
AI safety becomes harder when decisions are distributed across autonomous agents controlled by different people or organisations. These agents may be software services, robots, decision-support systems, or human decision makers. Harm can emerge even when no single agent clearly causes it, especially when knowledge is incomplete, tasks are delegated, and several agents could jointly intervene. Existing approaches often analyse causal contribution, assigned duties, or strategic ability separately, leaving gaps between who caused an outcome, who could have prevented it, and who ought to answer for it.
This project will develop an integrated framework for detecting and addressing responsibility gaps in multiagent systems. It will examine three linked challenges:
- responsibility for unanticipated harm and negligence
- collective responsibility when intervention requires a coalition
- attribution under uncertainty and partial observability
You may focus on one or more challenges while contributing to a shared formal model. Methods may include game theory, temporal, epistemic and deontic logics, formal verification, theorem proving, automated reasoning, and agent-based simulation. The work will connect prospective responsibility, identifying who must monitor or intervene before harm, with retrospective responsibility, attributing failures afterwards.
Expected outputs include formal definitions, attribution algorithms, an automated reasoning prototype, formal guarantees, simulation-based evaluation, and guidance on the information and logging needed for accountable oversight and control. Case studies may involve AI-assisted healthcare, shared-control autonomous systems, and AI-supported building management.
You will participate in doctoral training and research seminars within Electronics and Computer Science and the Agents, Interaction and Complexity group. Further development opportunities will include academic writing, responsible research and innovation, conference participation, public engagement, and interaction with researchers and stakeholders working on responsible AI and autonomous systems.
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent, in one of the following:
- computer science
- artificial intelligence
- mathematics
- engineering
- a closely related discipline
You should have strong analytical skills and an interest in mathematically grounded AI research. You should be willing to develop formal models and implement computational prototypes.
Experience in one or more of the following areas is desirable but not essential:
- multiagent systems
- mathematical or computational logic
- game theory
- formal verification or model checking
- automated reasoning or theorem proving
- agent-based modelling
- AI safety, responsible AI, or autonomous systems
Programming experience and evidence of independent research ability will be advantageous. A relevant master's degree is desirable but not essential.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
You need to:
- choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- search for programme PhD Computer Science (7089)
- add name of the supervisor in section 2 of the application
Applications should include:
- research proposal
- your CV (resumé)
- 2 academic references
- degree transcripts and certificates to date
- English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
If you have a general question, [contact details available in the full listing].
Project leader
For an initial conversation, [contact details available in the full listing].
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees' well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
