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: Coordination Layer: Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local
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to human and environmental interactions across various sectors such as healthcare, education, and urban planning. The primary aim of this project is to develop Multi-Intelligence Agents (MIAs) that combine
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vulnerabilities. Frontier models show superior performance when combined with a focused knowledge base and multi-agent architectures. However, in most cases human involvement is still required, and fully autonomous
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that are conducive to successful completion of the problem at hand. Particular focus will be on multi-robot and multi-agent problems (e.g., navigation, cooperative transport, team-based agent games). The ideal
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical