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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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– Hereby we offer a PhD Thesis focusing on the topic of Transport Modelling for Sustainable Mobility . Our main goal is to further develop and apply the agent-based simulation framework MATSim. The existing
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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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-Vietnam collaboration, funded by the Research Council of Norway (RCN). The successful candidate will use public health data from Vietnam to develop hybrid agent-based and system dynamics models
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to develop hybrid agent-based and system dynamics models. These models will then be adapted and applied to other ComDisp case studies in the USA, Ecuador, and Turkey. The PhD candidate will be responsible
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Applying guide Study abroad and exchange Events Ask us a question Agent resources Short courses and professional education Short courses and professional education Bringing together knowledge from across
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modification of the environment and content — creating a closed-loop learning system. Human-Robot Interaction (HRI): The learning environment may include robotic agents that interact with the learner. Here
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and