Minimizing Escape Probabilities: A Large Deviations Approach,
Abstract
This document considers the problem of controlling a possibly degenerate diffusion process so as to minimize the probability of escape over a given time interval. It is assumed that the control acts on the process through the drift coefficient, and that the noise coefficient is small. By developing a large deviations type theory for the controlled diffusion, the authors obtain several results. The limit of the normalized log of the minimum exit probability is identified as the value I of an associated (deterministic) differential game. Furthermore, the authors identify a deterministic (and epsilon independent) mapping g from the sample values epsilon w (s), 0 < or = S > or = t, into the control space such that if we define the control used at time t by u(t) = g(epsilon w(s), 0 < or = S , or = t), then the resulting control process is progressively measurable and delta optimal (in the sense that the limit of the normalized log of the exit probability is within delta of I).
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1987
- Accession Number
- ADA194534
Entities
People
- Harold Kushner
- Paul Dupuis
Organizations
- Brown University