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个人简介
My research focuses mainly on (deep) reinforcement learning, multi-agent systems, interactive machine learning, and curriculum learning. My primary research goal is to develop reinforcement learning algorithms that are more sample-efficient, robust, and scalable, with or without interacting with humans. During my postdoc, I worked mainly on developing new deep multi-agent reinforcement learning algorithms for discrete and continuous cooperative multi-agent tasks. My PhD research focuses on interactive machine learning and curriculum learning, where we study how non-expert humans want to teach the agent to solve new complex sequential decision making tasks and how to incorporate these insights into the development of new machine learning algorithms.
研究兴趣
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ARTIFICIAL INTELLIGENCE XL, AI 2023 (2023): 321-334
arxiv(2021)
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