Mindful Decisions: Theory of Mind–Enhanced Decision-Making and Cooperation in Autonomous Systems (Funded PhD) Ref: 5837

Supervisors

Dr Huma Samin, Department of Computer Science, University of Exeter 

Prof Andrew Howes, Department of Computer Science, University of Exeter 

The increasing prevalence of autonomous systems in dynamic, human-centred environments, such as smart transportation networks and distributed IoT infrastructures, demands decision-making frameworks that can anticipate and adapt to the behaviour of humans and other autonomous agents. This PhD project aims to investigate the integration of Theory of Mind (ToM) reasoning into autonomous agents to improve both individual decision-making and multi-agent cooperation.

The student will investigate two complementary directions:

1. ToM-Enhanced Decision-Making for Autonomous Agents:
   • Develop decision-making algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals.
   • Enable agents to simulate and adapt to human responses in real-time collaborative scenarios, enhancing performance in environments like smart transport systems, dynamic crowd management and other IoT-enabled infrastructures.
2. ToM-Enabled Multi-Agent Cooperation:
   • Equip autonomous agents to model the mental states of other agents, allowing prediction of behaviours, conflict resolution, and coordinated joint decision-making.
   • Evaluate performance in scenarios such as shared resource management, traffic coordination, and distributed IoT control, benchmarking ToM-enabled agents against traditional multi-agent systems.

Methodology:

• Integrate ToM models with Reinforcement Learning based frameworks for single-agent and multi-agent decision-making.
• Develop simulation environments capturing realistic human-agent and agent-agent interactions.
• Evaluate performance using metrics such as task success rates, coordination efficiency, and conflict resolution effectiveness.

Expected Contributions:

• A novel framework for ToM-enhanced autonomous decision-making.
• Mechanisms for ToM-based multi-agent coordination and conflict resolution.
• Benchmarked evaluation of ToM-enabled agents in simulated human-agent and multi-agent scenarios.

Opportunities for the Student:

• Gain expertise in AI planning, cognitive modelling, and multi-agent systems.
• Work on a real-world case study provided by the industrial partner British Telecom, bridging theory and practice.
• Contribute to cutting-edge research in the domain of autonomous systems.

The studentship will be awarded on the basis of merit. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide cover for Home fees and stipend.

International applicants need to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.   

Entry requirements

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in  Computer Science.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information.

How to apply

Apply now

To apply, please click the ‘Apply Now’ button above. In the application process you will be asked to upload several documents 

•             CV

•             Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project.

•             Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)

•             Two references from referees familiar with your academic work. If your referees prefer, they can email the reference direct to PGRApplicants@exeter.ac.uk quoting the studentship reference number.

•             If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

The closing date for applications is midnight on 14/04/2026.  Date for interviews are TBC. 

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

Please quote reference 5837 on your application and in any correspondence about this studentship.

Summary