Emergence of Norms with Biased Interactions in Heterogeneous Agent Societies

Effective norms, emerging from sustained individual interactions over time, can complement societal rules and significantly enhance performance of individual agents and agent societies. We have recently used a model that supports the emergence of social norms via learning from interaction experiences (Sen and Airiau, 2007). Each interaction is framed as a stage game. An agent learns a policy to play the game from repeated interactions with multiple agents. We are particularly interested in finding out if the entire population learns to converge to a consistent norm when multiple action combinations yield the same optimal payoff. In this extension, we explore the effects of heterogeneous populations where different agents may be using different learning algorithms. We also investigate norm emergence when an agent is more likely to interact with other agents near by it.