Social norms and cooperation in a collective-risk social dilemma : Comparing reinforcing learning and norm-based approaches

• Human cooperation is both powerful and puzzling. Large-scale cooperation among genetically unrelated individuals makes humans unique with respect to all other animal species. Therefore, learning how cooperation emerges and persists is a key question for social scientists. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking.We present here a version of the Experience-Weighted Attraction (EWA) reinforcement learning model that integrates norm-based considerations into its utility function that we call EWA+Norms. We compare the behaviour of this hybrid model to the standard EWA when applied to a collective risk social dilemma in which groups of individuals must reach a threshold level of cooperation to avoid the risk of catastrophe. We find that standard EWA is not sufficient for generating cooperation, but that EWA+Norms is. Next step is to compare simulation results with human behaviour in large-scale experiments.

Ämnesord

SAMHÄLLSVETENSKAP  -- Annan samhällsvetenskap (hsv//swe)

SOCIAL SCIENCES  -- Other Social Sciences (hsv//eng)

Nyckelord

Agricultural robots

Behavioral research

Disaster prevention

Reinforcement learning

Water management

Collective action

Human behaviours

Large scale experiments

Reinforcement learning models

Social scientists

Threshold levels

Utility functions

Well-founded models

Social robots

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