## Abstract

In this paper, we study a class of stochastic optimal control problem with jumps under partial information. More precisely, the controlled systems are described by a fully coupled nonlinear multi- dimensional forward-backward stochastic differential equation driven by a Poisson random measure and an independent multi-dimensional Brownian motion, and all admissible control processes are required to be adapted to a given subfiltration of the filtration generated by the underlying Poisson random measure and Brownian motion. For this type of partial information stochastic optimal control problem, we give a necessary and sufficient maximum principle. All the coefficients appearing in the systems are allowed to depend on the control variables and the control domain is convex.

Original language | English |
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Title of host publication | Proceedings of the 30th Chinese Control Conference, CCC 2011 |

Place of Publication | Piscataway, NJ |

Publisher | Institute of Electrical and Electronics Engineers (IEEE) |

Pages | 1317-1322 |

Number of pages | 6 |

ISBN (Electronic) | 9789881725592 |

ISBN (Print) | 9781457706776 |

Publication status | Published - 2011 |

Event | 30th Chinese Control Conference, CCC 2011 - Yantai, China Duration: 22 Jul 2011 → 24 Jul 2011 |

### Other

Other | 30th Chinese Control Conference, CCC 2011 |
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Country/Territory | China |

City | Yantai |

Period | 22/07/11 → 24/07/11 |

## Keywords

- Backward stochastic differential equation
- Maximum principle
- Partial information
- Poisson process
- Stochastic optimal control