We present a generalization of the classic Differential Dynamic Programming algorithm. We assume the existence of state- and control-dependent process noise, and proceed to derive the second-order expansion of the cost-to-go. Despite having quartic and cubic terms in the initial expression, we show that these vanish, leaving us with the same quadratic structure as standard DDP.
| Author(s): | Theodorou, E. and Tassa, Y. and Todorov, E. |
| Book Title: | In the proceedings of American Control Conference (ACC 2010) |
| Year: | 2010 |
| Bibtex Type: | Article (article) |
| Cross Ref: | p10307 |
| Electronic Archiving: | grant_archive |
| Note: | clmc |
| Links: | |
BibTex
@article{EvangelosACC2010,
title = {Stochastic Differential Dynamic Programming},
booktitle = {In the proceedings of American Control Conference (ACC 2010) },
abstract = {We present a generalization of the classic Differential Dynamic Programming algorithm. We assume the existence of state- and control-dependent process noise, and proceed to derive the second-order expansion of the cost-to-go. Despite having quartic and cubic terms in the initial expression, we show that these vanish, leaving us with the same quadratic structure as standard DDP.
},
year = {2010},
note = {clmc},
slug = {evangelosacc2010},
author = {Theodorou, E. and Tassa, Y. and Todorov, E.},
crossref = {p10307}
}