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Parallel Hierarchical Pre-Gauss-Seidel Value Iteration Algorithm

Author

Listed:
  • 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)

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.

Suggested Citation

  • Sanaa Chafik & Abdelhadi Larach & Cherki Daoui, 2018. "Parallel Hierarchical Pre-Gauss-Seidel Value Iteration Algorithm," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 10(2), pages 1-22, April.
  • Handle: RePEc:igg:jdsst0:v:10:y:2018:i:2:p:1-22
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