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College Colloquium——Risk-sensitive Markov decision processes in continuous-time

发布日期:2021-05-25点击数:

报告人:郭先平(中山大学)

时间:2021年5月28日09:00开始

腾讯会议ID:171 808 472

会议链接:https://meeting.tencent.com/s/rkMRRiZAYvmd


摘要:This talk is on the risk-sensitive continuous-time Markov decision processes with unbounded transition and discounted costs. 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.


简介:郭先平,男,博士,博士生导师,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团队助计划,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,现为全国概率统计学会副理事长。曾担任国际(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。


邀请人:周国立


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