The Adjoint Process in Stochastic Optimal Control.
Abstract
The focus of this research is the filtering jump processes. To investigate the filtering of manifold valued processes, their approximation by random walks and Markov chains was studied. The object was to approximate a signal process by a finite state jump process for which a finite dimensional filter is available. Four papers were published during the past year, including The existence of smooth densities for the prediction, filtering and smoothing problems and The partially observed stochastic minimum principle. Using stochastic flows a minimum principle is obtained when a diffusion is controlled using stochastic open loop controls. An equation for the adjoint process is then derived using an explicit formula for the integrand in a certain stochastic integral.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 11, 1987
- Accession Number
- ADA189720
Entities
People
- Michael Kohlmann
- Robert J. Elliott
Organizations
- University of Alberta