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A Dynamic Programming Based Solution to the Two-Dimensional Jump-It Problem

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Published:13 April 2017Publication History

ABSTRACT

This paper introduces the two-dimensional Jump-It problem, which is a board playing optimization problem. We present a dynamic programming based solution that finds the optimal cost of playing the game in O(mn), where m and n are the dimensions of the playing board. We also show how the solution can be extended to find a path that leads to playing the game with the optimal cost.

References

  1. Thomas Cormen, Charles Leiserson, Ronald Rivest, and Clifford Stein. 2009. Introduction to Algorithms, 3rd ed., Cambridge, MA: MIT Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Jon Kleinberg and Eva Tardos. 2005. Algorithm Design, Boston, MA: Pearson, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Jamil Saquer and Lloyd Smith. 2016. Simplifying dynamic programming, In Proceedings of the 5th International Conference on Informatics and Applications, Takamatsu, Japan, 159--164.Google ScholarGoogle Scholar
  4. Jamil Saquer and Razib Iqbal. 2017. A Python source code for finding an optimal path for the 2D JumpIt problem. {online} http://people.missouristate.edu/riqbal/algorithms/Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Conferences
    ACM SE '17: Proceedings of the SouthEast Conference
    April 2017
    275 pages
    ISBN:9781450350242
    DOI:10.1145/3077286

    Copyright © 2017 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 13 April 2017

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    • short-paper
    • Research
    • Refereed limited

    Acceptance Rates

    ACM SE '17 Paper Acceptance Rate 21 of 34 submissions, 62%Overall Acceptance Rate 103 of 169 submissions, 61%
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