Mu Lab
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About
Mu Lab is a research laboratory specializing in Model Understanding, Multi-agent Reasoning, and Modeling Uncertainty. Led by Prof. Christian Muise at Queen's University, the lab conducts cutting-edge research across various AI domains. Their projects include advancing FOND Planning with PR2, implementing LOCM Action Model Acquisition, and developing Continuous Authentication systems using typing gait recognition. Publications highlight the use of Large Language Models for fixing ill-defined models, generating PDDL models, and constructing automated planning models. The lab also works on goal-directed dialogue systems for safety-critical applications. Mu Lab aims to push the boundaries of AI research through its diverse projects and academic contributions.
Platform
Features
• goal-directed dialogue system development
• llm-based model fixing and generation
• continuous user authentication
• action model acquisition (locm)
• automated planning advancement (fond, pddl)
• modeling uncertainty research
• multi-agent reasoning research
• model understanding research
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