Parallel Hierarchical Pre-Gauss-Seidel Value Iteration Algorithm

Sanaa Chafik, Abdelhadi Larach and Cherki Daoui
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Sanaa Chafik: Sultan Moulay Slimane University, Beni Mellal, Morocco
Abdelhadi Larach: Sultan Moulay Slimane University, Beni Mellal, Morocco
Cherki Daoui: Department of Mathematics, Sultan Moulay Slimane University, Beni Mellal, Morocco

International Journal of Decision Support System Technology (IJDSST), 2018, vol. 10, issue 2, 1-22

Abstract: The 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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:10:y:2018:i:2:p:1-22

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