Web: http://arxiv.org/abs/2206.07376

June 16, 2022, 1:10 a.m. | Xiaoteng Ma, Shuai Ma, Li Xia, Qianchuan Zhao

cs.LG updates on arXiv.org arxiv.org

Keeping risk under control is often more crucial than maximizing expected
reward in real-world decision-making situations, such as finance, robotics,
autonomous driving, etc. The most natural choice of risk measures is variance,
while it penalizes the upside volatility as much as the downside part. Instead,
the (downside) semivariance, which captures negative deviation of a random
variable under its mean, is more suitable for risk-averse proposes. This paper
aims at optimizing the mean-semivariance (MSV) criterion in reinforcement
learning w.r.t. steady rewards. …

arxiv learning lg mean optimization policy reinforcement reinforcement learning risk

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