Silly rules improve the capacity of agents to learn stable enforcement and compliance behaviors
This addresses the problem of understanding norm emergence in multi-agent systems, with incremental insights into social learning dynamics.
The study tackled how societies learn to enforce and comply with social norms in a multi-agent foraging game, finding that introducing an arbitrary taboo (a 'silly rule') improved the rate and stability of learning to punish violations and comply with taboos, achieving better outcomes in middle learning stages.
How can societies learn to enforce and comply with social norms? Here we investigate the learning dynamics and emergence of compliance and enforcement of social norms in a foraging game, implemented in a multi-agent reinforcement learning setting. In this spatiotemporally extended game, individuals are incentivized to implement complex berry-foraging policies and punish transgressions against social taboos covering specific berry types. We show that agents benefit when eating poisonous berries is taboo, meaning the behavior is punished by other agents, as this helps overcome a credit-assignment problem in discovering delayed health effects. Critically, however, we also show that introducing an additional taboo, which results in punishment for eating a harmless berry, improves the rate and stability with which agents learn to punish taboo violations and comply with taboos. Counterintuitively, our results show that an arbitrary taboo (a "silly rule") can enhance social learning dynamics and achieve better outcomes in the middle stages of learning. We discuss the results in the context of studying normativity as a group-level emergent phenomenon.