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Distributed Nested Rollout Policy for SameGame

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Computer Games (CGW 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 818))

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Abstract

Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search heuristic for puzzles and other optimization problems. It achieves state-of-the-art performance on several games including SameGame. In this paper, we design several parallel and distributed NRPA-based search techniques, and we provide a number of experimental insights about their execution. Finally, we use our best implementation to discover 15 better scores for 20 standard SameGame boards.

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Notes

  1. 1.

    CPU: Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40 GHz.

  2. 2.

    https://en.wikipedia.org/wiki/Hyper-threading.

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Acknowledgments

Experiments presented in this paper were carried out using the Grid’5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several universities as well as other organizations (see https://www.grid5000.fr).

Author information

Authors and Affiliations

  1. PSL Université Paris-Dauphine, LAMSADE UMR CNRS 7243, Place du Maréchal de Lattre de Tassigny, 75775, Paris Cedex 16, France

    Benjamin Negrevergne & Tristan Cazenave

Authors
  1. Benjamin Negrevergne
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  2. Tristan Cazenave
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Corresponding author

Correspondence to Benjamin Negrevergne .

Editor information

Editors and Affiliations

  1. Université Paris-Dauphine, Paris, France

    Tristan Cazenave

  2. Maastricht University, Maastricht, The Netherlands

    Mark H.M. Winands

  3. The University of New South Wales, Sydney, New South Wales, Australia

    Abdallah Saffidine

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Negrevergne, B., Cazenave, T. (2018). Distributed Nested Rollout Policy for SameGame. In: Cazenave, T., Winands, M., Saffidine, A. (eds) Computer Games. CGW 2017. Communications in Computer and Information Science, vol 818. Springer, Cham. https://doi.org/10.1007/978-3-319-75931-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-75931-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75930-2

  • Online ISBN: 978-3-319-75931-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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