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DRIS: Direct Reciprocity Based Image Score Enhances Performance in Collaborate Computing System

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Collaborate Computing: Networking, Applications and Worksharing (CollaborateCom 2016)

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Abstract

The key issue in collaborate computing systems is to induce agents work together towards a common task. Indirect reciprocity is a widely used method to promote cooperation. Image score is a classic indirect reciprocity mechanism which provided an insight on promoting cooperation. However, intuitively, people trust their own feelings more than other’s opinions. Thus, in this paper, we introduce direct reciprocity into image score: when granting a service, a player should consider their own interaction histories in priority and consider image score if they have no interactions before. Extensive simulation results show that our proposed model can more effectively promote cooperation than classic image score under both complete and incomplete information.

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Acknowledgment

This paper is supported by the National Science Foundation of China under grant No. 61272173, 61403059, 61572095.

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Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, 116620, Liaoning, China

    Kun Lu, Shiyu Wang & Qilong Zhen

Authors
  1. Kun Lu
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  2. Shiyu Wang
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  3. Qilong Zhen
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Corresponding author

Correspondence to Kun Lu .

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Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Ao Zhou

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lu, K., Wang, S., Zhen, Q. (2017). DRIS: Direct Reciprocity Based Image Score Enhances Performance in Collaborate Computing System. In: Wang, S., Zhou, A. (eds) Collaborate Computing: Networking, Applications and Worksharing. CollaborateCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 201. Springer, Cham. https://doi.org/10.1007/978-3-319-59288-6_48

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  • DOI: https://doi.org/10.1007/978-3-319-59288-6_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59287-9

  • Online ISBN: 978-3-319-59288-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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