中山大学郭先平教授学术报告 11月7日上午

发布时间:2020-11-03浏览次数:401

概率统计系列讲座十五:


报告题目【Risk-sensitive discounted continuous-time Markov decision processes】

时间:2020年11月07日 (星期六)上午 09:00 

地点:腾讯会议(会议 ID:511 3889 6273)

报告人:中山大学教授,郭先平

主办:数学与信息学院

参加对象:统计系老师与学生


报告摘要:This talk is on the risk-sensitive discounted continuous-time Markov decision processes with unbounded transition and cost rates. Different from the case of bounded transition/cost rates, the optimality equation (OE) no longer has a solution satisfying the uniform convergent condition introduced in the existing literature. Thus, we first replace the uniform convergent condition of the solution with a suitable weighted-bound. Then, we find mild conditions imposed on the primitive data of the decision processes, which not only ensure the existence of a solution to the OE but also are the generalization of the bounded transition/cost rates conditions. Furthermore, using the characterization of the weighted-bound and a novel technique, from the OE we prove the existence of an optimal policy out of the class of randomized history-dependent policies. Finally, we present two examples with unbounded transition/cost rates to illustrate our results.


报告人简介:郭先平,男,博士,博士生导师,国家杰出青年科学基金获得者, 1996年于中南大学获博士学位,2002于中山大学晋升为教授,2003年入选教育部优秀青年教师资助计划,2004年入选教育部新世纪优秀人才支持计划,2010年被评为珠江学者特聘教授。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》、《应用概率统计》、《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、排队优化等。