Guided Policy Search for Sequential Multitask Learning
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DOI: 10.1109/tsmc.2018.2800040
Abstract: Policy search in reinforcement learning (RL) is a practical approach to interact directly with environments in parameter spaces, that often deal with dilemmas of local optima and real-time sample collection. A promising algorithm, known as… read more here.
Keywords: sequential multitask; multitask learning; policy search;