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Competitive Analysis of the Windfall Game

  • Conference paper
Fun with Algorithms (FUN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8496))

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Abstract

We study the classical computer game ”Super Mario Power Coins” as an online maximization problem with look-ahead. We show nearly matching lower and upper bounds for deterministic online algorithms.

RF acknowledges support by the National Natural Science Foundation of China (No. 60973026), the Shanghai Leading Academic Discipline Project (project number B114), the Shanghai Committee of Science and Technology of China (09DZ2272800), the Robert Bosch Foundation (Science Bridge China 32.5.8003.0040.0), and the Research Council (TRC) of the Sultanate of Oman.

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References

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  4. Super Mario Power Coins (2010), http://www.onlinegames.net/games/961/super-mario-power-coins.html

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Author information

Authors and Affiliations

  1. School of Computer Science, IIPL, Fudan University, Shanghai, China

    Rudolf Fleischer

  2. CS Department, GUtech, Muscat, Oman

    Rudolf Fleischer

  3. PICB, Shanghai, China

    Tao Zhang

Authors
  1. Rudolf Fleischer
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  2. Tao Zhang
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Editor information

Editors and Affiliations

  1. Dipartimento di Matematica e Informatica, Città Universitaria, Università degli Studi di Catania, Viale A. Doria, 6, 95125, Catania, Italy

    Alfredo Ferro

  2. Dipartimento di Informatica, Università di Pisa, Largo B. Pontecorvo 3, 56127, Pisa, Italy

    Fabrizio Luccio

  3. Institute of Theoretical Computer Science, ETH Zürich, Universitätsstrasse 6, 8092, Zürich, Switzerland

    Peter Widmayer

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© 2014 Springer International Publishing Switzerland

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Fleischer, R., Zhang, T. (2014). Competitive Analysis of the Windfall Game. In: Ferro, A., Luccio, F., Widmayer, P. (eds) Fun with Algorithms. FUN 2014. Lecture Notes in Computer Science, vol 8496. Springer, Cham. https://doi.org/10.1007/978-3-319-07890-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-07890-8_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07889-2

  • Online ISBN: 978-3-319-07890-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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