Name
Abstract | ||
|---|---|---|
AbstractThe standard Value Iteration VI algorithm, referred to as Value Iteration Pre-Jacobi PJ-VI algorithm, is the simplest Value Iteration scheme, and the well-known algorithm for solving Markov Decision Processes MDPs. In the literature, several versions of VI algorithm were developed in order to reduce the number of iterations: the VI Jacobi VI-J algorithm, the Value Iteration Pre-Gauss-Seidel VI-PGS algorithm and the VI Gauss-Seidel VI-GS algorithm. In this article, the authors combine the advantages of VI Pre Gauss-Seidel algorithm, the decomposition technique and the parallelism in order to propose a new Parallel Hierarchical VI Pre-Gauss-Seidel algorithm. Experimental results show that their approach performs better than the traditional VI schemes in the case where the global problem can be decomposed into smaller problems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.4018/IJDSST.2018040101 | Periodicals |
Keywords | Field | DocType |
Decomposition, Hierarchical Algorithm, Markov Decision Process, Markov Model, Parallel Hierarchical Algorithm, Parallelism, Pre-Gauss-Seidel, Value Iteration | Computer science,Markov decision process,Algorithm,Gauss–Seidel method | Journal |
Volume | Issue | ISSN |
10 | 2 | 1941-6296 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanaa Chafik | 1 | 1 | 1.70 |
| Abdelhadi Larach | 2 | 0 | 0.34 |
| Cherki Daoui | 3 | 0 | 1.01 |