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On the effect of memory on the Prisoner’s Dilemma game in correlated networks

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  • Lotfi, Nastaran
  • Rodrigues, Francisco A.

Abstract

Game theory is fundamental to understanding cooperation between agents. The Prisoner’s Dilemma is a well-known model extensively studied in complex networks. However, previous works ignore players’ memory, and the decisions about the strategies are based only on the latest games. At the same time, in real-world games, players generally consider the current situation and previous experiences when deciding their strategy. In this paper, we study how memory influences cooperation in correlated networks. We consider the evolutionary Prisoner’s Dilemma game on random and scale-free networks presenting degree–degree correlation. Through extensive simulations, we show that assortativity can improve cooperation when the temptation to defect increases. Moreover, our results suggest that including memory decreases the network structure’s influence on cooperation. Our study contributes to understanding the role of the network topology and the player’s memory on cooperation.

Suggested Citation

  • Lotfi, Nastaran & Rodrigues, Francisco A., 2022. "On the effect of memory on the Prisoner’s Dilemma game in correlated networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007208
    DOI: 10.1016/j.physa.2022.128162
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    References listed on IDEAS

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    1. Chen, Xiaojie & Fu, Feng & Wang, Long, 2007. "Prisoner's Dilemma on community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 512-518.
    2. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    3. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
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    2. Duan, Yuxian & Huang, Jian & Zhang, Jiarui, 2023. "Evolutionary public good games based on the long-term payoff mechanism in heterogeneous networks," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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