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 |
|---|---|
| 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