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] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference on Electronic Commerce.” Accessed September 10, 2021. https://dl-acm
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] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference on Electronic Commerce.” Accessed September 10, 2021. https://dl-acm
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learning-based strategic behavior in multi-agent settings and on designing market rules that ensure stable, efficient, and safe operation of critical infrastructure. The work combines theory and
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synthetic populations and mobility digital twins for resilient and equitable transport planning. The project combines agent-based modelling, large-scale mobility data, transport networks, generative
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synthetic populations and mobility digital twins for resilient and equitable transport planning. The project combines agent-based modelling, large-scale mobility data, transport networks, generative
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applications based on this theory [2]. The ultimate goal of this project is to develop new computational methods for modelling social dilemmas that can account for real-world complexity in agents
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specifically interested in: Data-centric AI: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety : Ensuring robust alignment and safety in multi-agent LLM
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machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety : Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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: Do you have a background in energy informatics, computer science, or energy systems, and are you are interested in edge intelligence, multi-agent AI, and interdisciplinary collaborative research
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environments. The project will explore how learning-based and agentic AI systems (e.g., agents built on large language or foundation models) can be combined with physics-informed process models, digital