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This model accompanies a paper looking at the role and limits of values and norms for modeling realistic social agents. Based on literature we synthesize a theory on norms and a theory that combines both values and norms. In contrast to previous work, these theories are checked against data on human behavior obtained from a psychological experiment on dividing money: the ultimatum game. We found that agents that act according to a theory that combines both values and norms, produce behavior quite similar to that of humans. Furthermore, we found that this theory is more realistic than theories solely concerned with norms or theories solely concerned with values. However, to explain the amount of money people accept in this ultimatum game we will eventually need an even more realistic theory. We propose that a theory that explains when people exactly choose to use norms instead of values could provide this realism.
The Social Practice Agent (SoPrA) model enables the use of social practice theory (SPT) for agent-based simulations (ABS). SoPrA is the first computational agent model that combines the habitual, social and interconnected aspects of behaviour and provides a starting point for ABS researchers to model social phenomena.
The model is accompanied with a paper. We describe literature on SPT and agent theory
and distill requirements for modelling habitual, social and interconnected behaviour. We construct the SoPrA
model that satisfies the requirements and present the model in the Unified Modelling Language. We discuss
modelling choices, an implementation in Netlogo, Repast and Protégé, compare SoPrA to other socio-cognitive