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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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-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
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severity ranking in video games. The research will implement a multi-agent workflow with three complementary roles: an Explorer agent that actively probes the game to discover failures; an Inspector agent
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the next generation of human-centred industrial systems? We are seeking a talented PhD student to investigate Agentic AI for human–robot collaboration, focusing on how intelligent machines can understand
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harmonize datasets across institutional and external sources (e.g., advising, curriculum, learning platforms, labor-market data), including secure handling and anonymization when needed. AI/agentic system
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community of staff are united by our purpose to inspire Australia’s future change-makers and create a better tomorrow. Work that matters Advance the frontier of AI by developing multi-agent systems capable
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://cavecore.eu/ Your Research Project (DC4) You will work at the intersection of machine learning, control theory, and autonomous multi-agent systems to develop hybrid learning-based control strategies
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implements multi-agent systems to optimize clinical decision support and patient monitoring. Rigorous testing of AI safety protocols ensures the reliability and ethical deployment of these autonomous models
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behaviours of multi-agent systems in response to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be
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for Enhancing Decision-Making in Networks of Autonomous Agents”, which aims to develop a new methodological framework to improve decision-making in autonomous systems. The project combines high-frequency radio