| Full text | |
| Author(s): |
Arruda, Edilson R.
;
do Val, Joao B. R.
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14; v. N/A, p. 2-pg., 2006-01-01. |
| Abstract | |
We present a general method to obtain convergent approximate value iteration algorithms with function approximation. The result is applicable to any arbitrary approximation architecture and generalizes existing results in the literature derived for particular approximation schemes. Additionally, we show how to obtain a convergent approximate mapping whose fixed point is the projection in the approximation space of a fixed point of the exact dynamic programming mapping with regards to a suitable subset norm. This result relies on evaluating the difference between successive iterates in the selected subset norm, which provides convergent procedures for any arbitrary approximation architecture. (AU) | |
| FAPESP's process: | 03/06736-7 - Control and filtering of Markovian jumping parameters stochastic systems |
| Grantee: | João Bosco Ribeiro do Val |
| Support Opportunities: | Research Projects - Thematic Grants |