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Computational Modelling of Trust and Social Relationships

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Abstract

A computational model for the development of social relationships is described. The model implements agent strategies for social interaction based on Dunbar's Social Brain Hypothesis (SBH). A trust related process controls the formation and decay of relationships as a function of interaction frequency, the history of interaction, and the agents' strategies. A good fit the SBH predictions was found across a range of model parameter settings, which varied the waning rate of trust, defect/cooperation rates for agents, and linear/log functions for trust increase and decay. Social interaction strategies which favour interacting with existing strong ties or a time variant strategy produced more SBH conformant results than strategies favour more weaker relationships. The prospects for modeling the emergence of social relationships are discussed.

Suggested Citation

  • Alistair Sutcliffe & Di Wang, 2012. "Computational Modelling of Trust and Social Relationships," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-3.
    • Handle: RePEc:jas:jasssj:2010-90-3
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    3. Martin A. Nowak & Karl Sigmund, 2005. "Evolution of indirect reciprocity," Nature, Nature, vol. 437(7063), pages 1291-1298, October.
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    1. Ahmadreza Asgharpourmasouleh & Atiye Sadeghi & Ali Yousofi, 2017. "A Grounded Agent-Based Model of Common Good Production in a Residential Complex: Applying Artificial Experiments," SAGE Open, , vol. 7(4), pages 21582440177, October.
    2. Shu-Heng Chen & Bin-Tzong Chie & Tong Zhang, 2015. "Network-Based Trust Games: An Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-5.

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