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evolutionary and behavioural game theory, multi-agent reinforcement learning, agent-based simulation, or experiments with people and AI systems. Some students may develop new theory or algorithms; others may use
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natural language processing, multi-agent systems, reinforcement learning, or knowledge representation would be advantageous but is not strictly required. Strong analytical and problem-solving abilities, as
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trustworthy decision support. This PhD project aims to develop next-generation Trustworthy Agentic AI frameworks that integrate multi-agent collaboration, large language models, retrieval-augmented generation
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of cybersecurity where AI systems are no longer passive detection tools, but active cyber defenders. The project investigates how large language models, multi-agent systems, reinforcement learning, and secure
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This project aims to combine causal analysis, large language models (LLMs), and multi-agent reasoning to accelerate scientific discovery in mental health support. Modern psychiatry and clinical
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on social dilemmas, i.e., situations where poor group outcomes arise from optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social Systems, and Models in Biology and
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The multi-agent path finding problem (MAPF) asks us to find a collision-free plan for a team of moving agents. Such problems appear in many application settings (including robotics, logistics