Norm emergence with biased agents

Effective norms can significantly enhance performance of individual agents and agent societies. We consider individual agents that repeatedly interact over instances of a given scenario. Each interaction is framed as a stage game where multiple action combinations yield the same optimal payoff. An agent learns to play the game over repeated interactions with multiple, unknown, agents. The key research question is to find out whether a consistent norm emerges when all agents are learning at the same time. In real-life, agents may have pre-formed biases or preferences which may hinder or even preclude norm emergence. We study the success and speed of norm emergence when different subsets of the population have different initial biases. In particular we characterize the relative speed of norm emergence under varying biases and the success of majority/minority groups in enforcing their biases on the rest of the population given different bias strengths.