Mu Lab
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About
Mu Lab focuses on exploring various advanced topics in artificial intelligence, particularly in model understanding, multi-agent reasoning, and modeling uncertainty. Their projects include innovative research on FOND planning, action model acquisition, and continuous user authentication through typing gait recognition. The lab has authored several publications on topics like goal-directed dialogue systems and deep reinforcement learning for autonomous navigation. Led by Professor Christian Muise, the lab includes various PhD and master's students who contribute to ongoing research.
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Features
• research publications
• multi-agent reasoning
• modeling uncertainty
• model understanding
• project collaboration
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