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  • 标题:Probabilistic interpretation of HJB equations by the representation theorem for generators of BSDEs
  • 本地全文:下载
  • 作者:Lishun Xiao ; Shengjun Fan ; Dejian Tian
  • 期刊名称:Electronic Communications in Probability
  • 印刷版ISSN:1083-589X
  • 出版年度:2020
  • 卷号:25
  • DOI:10.1214/20-ECP310
  • 语种:English
  • 出版社:Electronic Communications in Probability
  • 摘要:The purpose of this note is to propose a new approach for the probabilistic interpretation of Hamilton-Jacobi-Bellman equations associated with stochastic recursive optimal control problems, utilizing the representation theorem for generators of backward stochastic differential equations. The key idea of our approach for proving this interpretation lies in the identity between solutions and generators given by the representation theorem. Compared with existing methods, our approach seems to be a feasible unified method for different frameworks and be more applicable to general settings. This can also be regarded as a new application of such representation theorem.
  • 关键词:backward stochastic differential equation; recursive optimal control problem; Hamilton-Jacobi-Bellman equation; representation theorem for generator
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