| Article ID: | iaor1999901 |
| Country: | United States |
| Volume: | 65 |
| Issue: | 3 |
| Start Page Number: | 487 |
| End Page Number: | 516 |
| Publication Date: | May 1997 |
| Journal: | Econometrica |
| Authors: | Rust J. |
| Keywords: | markov processes |
This paper introduces random versions of successive approximations and multigrid algorithms for computing approximate solutions to a class of finite and infinite horizon Markovian decision problems (MDPs). We prove that these algorithms succeed in breaking the ‘curse of dimensionality’ for a subclass of MDPs known as discrete decision processes.