Reinforcement learning algorithm for non-stationary environments
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DOI: 10.1007/s10489-020-01758-5
Abstract: Reinforcement learning (RL) methods learn optimal decisions in the presence of a stationary environment. However, the stationary assumption on the environment is very restrictive. In many real world problems like traffic signal control, robotic applications,… read more here.
Keywords: stationary environments; reinforcement learning; non stationary; optimal decisions ... See more keywords
Meta-Reinforcement Learning in Non-Stationary and Dynamic Environments
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3185549
Abstract: In recent years, the subject of deep reinforcement learning (DRL) has developed very rapidly, and is now applied in various fields, such as decision making and control tasks. However, artificial agents trained with RL algorithms… read more here.
Keywords: non stationary; reinforcement learning; stationary environments; task ... See more keywords