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DOI

Social simulations gain strength when agent behaviour can (1) represent human behaviour and (2) be explained in understandable terms. Agents with values and norms lead to simulation results that meet human needs for explanations, but have not been tested on their ability to reproduce human behaviour. This paper compares empirical data on human behaviour to simulated data on agents with values and norms in a psychological experiment on dividing money: the ultimatum game. We find that our agent model with values and norms produces aggregate behaviour that falls within the 95% confidence interval wherein human behaviour lies more often than other tested agent models. A main insight is that values serve as a static component in agent behaviour, whereas norms serve as a dynamic component.

Original languageEnglish
Article number9
JournalJASSS
Volume22
Issue number1
DOIs
Publication statusPublished - 2019

    Research areas

  • Agent-based model, Empirical data, Human values, Norms, Ultimatum game

ID: 52903074