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Various error settings bring different noise-driven effects on network reciprocity in spatial prisoner's dilemma

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  • Alam, Muntasir
  • Nagashima, Keisuke
  • Tanimoto, Jun

Abstract

In view of stochastic resonance effect, this paper reports what type of additional noise can draw more enhanced network reciprocity in spatial prisoner's dilemma (SPD) games presuming different underlying networks as well as strategy updating rules. Relying on a series of simulations comprehensively designed, we explored various noise models namely action error, copy error, observation error, by either placing random agents or biased agents and variant settings of those. We found that the influence by adding noise significantly differs depending on the type of noise as well as the combination of what underlying network and update rule are presumed. Action error when added to SPD games presuming deterministic updating rule shows relatively large enhancement for cooperation.

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  • Alam, Muntasir & Nagashima, Keisuke & Tanimoto, Jun, 2018. "Various error settings bring different noise-driven effects on network reciprocity in spatial prisoner's dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 338-346.
  • Handle: RePEc:eee:chsofr:v:114:y:2018:i:c:p:338-346
    DOI: 10.1016/j.chaos.2018.07.014
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    1. Keke Huang & Tao Wang & Yuan Cheng & Xiaoping Zheng, 2015. "Effect of Heterogeneous Investments on the Evolution of Cooperation in Spatial Public Goods Game," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-10, March.
    2. Markus Brede, 2013. "Short Versus Long Term Benefits and the Evolution of Cooperation in the Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    3. Zhang, Gui-Qing & Hu, Tao-Ping & Yu, Zi, 2016. "An improved fitness evaluation mechanism with noise in prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 276(C), pages 31-36.
    4. Zhang, Gui-Qing & Sun, Qi-Bo & Wang, Lin, 2013. "Noise-induced enhancement of network reciprocity in social dilemmas," Chaos, Solitons & Fractals, Elsevier, vol. 51(C), pages 31-35.
    5. EL-Seidy, Essam, 2015. "The effect of noise and average relatedness between players in iterated games," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 343-350.
    6. Kokubo, Satoshi & Wang, Zhen & Tanimoto, Jun, 2015. "Spatial reciprocity for discrete, continuous and mixed strategy setups," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 552-568.
    7. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    8. Yao, Yao & Chen, Shen-Shen, 2014. "Multiplicative noise enhances spatial reciprocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 432-437.
    9. Yokoi, Hiroki & Uehara, Takashi & Sakata, Tomoyuki & Naito, Hiromi & Morita, Satoru & Tainaka, Kei-ichi, 2014. "Evolution of altruism in spatial prisoner’s dilemma: Intra- and inter-cellular interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 361-370.
    10. Shen, Chen & Lu, Jun & Shi, Lei, 2016. "Does coevolution setup promote cooperation in spatial prisoner's dilemma game?," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 201-207.
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