Management System Engineering (Dec 2023)

Cooperation dynamics in public goods games with evolving cognitive bias

  • Ji Quan,
  • Haoze Li,
  • Xianjia Wang

DOI
https://doi.org/10.1007/s44176-023-00025-4
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 14

Abstract

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Abstract It has been proved that cognitive biases widely exist in various social realities and lead to unprecedented consequences by affecting individual judgment and decision-making processes in distinct ways. To further explore the influence of changeable cognitive bias, we introduce a heterogeneous population and learning process that can be influenced by cognitive bias into the threshold public goods game (TPGG). Specifically, additional parameters describing the heterogeneity and updating speed of bias are employed. The combined effects of bias and the inherent parameters in the TPGG model on the evolution of cooperation are explored. Numerical simulation results show that the heterogeneity of cognitive bias exhibits diametrically opposite effects when the threshold is relatively low and high, and the effect of incentives based on fixed reward and adjustable punishment are distorted by heterogeneous cognitive biases as well. In addition, the process of social learning forces individuals to update their beliefs toward the direction of obtaining a higher payoff. Different learning rates eventually lead to distinct levels of cooperation by changing the distribution of cognitive bias when the population reaches the evolutionary steady state. Our work extends the research framework on cognitive bias from the perspective of population heterogeneity and explores the impact of individuals' learning ability on personal bias and cooperative behavior.

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