Mu Lab
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About
Mu Lab is a leading research group dedicated to advancing the state of the art in Model Understanding, Multi-agent Reasoning, and Modeling Uncertainty. The lab's diverse projects encompass areas like FOND planning (PRP Rebooted), action model acquisition using the MACQ library (LOCM), and continuous authentication through typing gait recognition. Their impactful publications highlight innovative applications of Large Language Models (LLMs) for fixing ill-defined planning models (FixMyPlan), automating PDDL model generation (L2P), and surveying LLMs for planning. They also contribute to medical imaging with performance evaluation of stacked classifiers and develop goal-directed dialogue systems for safety-critical applications. Based at Queen's University, Mu Lab is actively shaping the future of AI research.
Platform
Task
Features
• continuous authentication
• automated pddl model generation
• large language model integration
• action model acquisition
• fond planning
• modeling uncertainty
• multi-agent reasoning
• model understanding
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