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researched by another PhD candidate in the project. The developed methods could be applicable across many multi-agent coordination domains, from mobiltiy, to logistics and multi-robot systems. In this work, we
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. Advertising images can also link products to ideas of success. Thus, these forms of communication are not merely tools for conveying messages, but powerful agents that sculpt our society, influence our
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multi-agent coordination domains, from mobiltiy, to logistics and multi-robot systems. In this work, we will consider two use cases: (1) a mobility network considering both fixed-line buses and on-demand
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design principles with stakeholder engagement approaches, ensuring that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent
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applications such as conversational agents, mental well-being, and education, where emotion safety is crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction
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and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore applications such as conversational agents, mental well-being, and education, where emotion safety is
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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interaction; Design methods and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore applications such as conversational agents, mental well-being, and education, where
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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data