摘要：In this talk, we will introduce a so-called average value-at-risk (AVaR)  optimization problem for semi-Markov decision processes (SMDPs), and aim at minimizing the AVaR of the finite horizon costs. The main goals of this talk are to show the approach for establishing the existence of an AVaR optimal policy and give algorithms of obtaining AVaR optimal policies. To demonstrate our results, an example about maintenance systems is provided.

 个人简介： 中山大学教授、博士生导师，国家杰出青年科学基金获得者，现担任中山大学数学学院副院长。担（曾）任国际（SCI）杂志 Advances in Applied Probability，Journal of Applied Probability，Science China Mathematics，Journal of Dynamics and Games，及国内期刊《中国科学：数学》、《应用数学学报》、《运筹学学报》等杂志编委.研究兴趣为马氏决策过程、随机博弈、风险控制等。

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