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The Machine Learning & Mind Lab is a research group focusing on fundamental machine learning algorithms for intelligent agents such as autonomous robots and virtual agents. Our research is at the intersection of machine learning, reinforcement learning, and robot learning. More specifically, the group focuses on how to learn structured general knowledge and representation of the world via interaction with the environment and then use the acquired knowledge to solve general problems. To tackle this challenge, we are focusing on representation learning, world model (common sense) learning, and reinforcement learning. We've been publishing in the top machine learning conferences such as NeurIPS, ICML, and ICLR.