Asymptotic optimal tracking: feedback strategies

被引:7
|
作者
Cai, Jiatu [1 ]
Rosenbaum, Mathieu [2 ,4 ]
Tankov, Peter [1 ,3 ]
机构
[1] Univ Paris Diderot Paris 7, Lab Probabilites & Modeles Aleatoires, Paris, France
[2] Univ Pierre & Marie Curie Paris 6, Lab Probabilites & Modeles Aleatoires, Paris, France
[3] CREST ENSAE ParisTech, 3 Ave Pierre Larousse, F-92240 Malakoff, France
[4] Ecole Polytech, CMAP, Paris, France
关键词
Tracking problem; asymptotic optimality; feedback strategies;
D O I
10.1080/17442508.2017.1285304
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This is a companion paper to [Cai, Rosenbaum and Tankov, Asymptotic lower bounds for optimal tracking: a linear programming approach, Arxiv: 1510.04295]. We consider a class of strategies of feedback form for the problem of tracking and study their performance under the asymptotic framework of the above reference. The strategies depend only on the current state of the system and keep the deviation from the target inside a time-varying domain. Although the dynamics of the target is non-Markovian, it turns out that such strategies are asympototically optimal for a large list of examples.
引用
收藏
页码:943 / 966
页数:24
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