Emergence of Norms through Social Learning

Behavioral norms are key ingredients that allow agent coordination where societal laws do not sufficiently constrain agent behaviors. Whereas social laws need to be enforced in a top-down manner, norms evolve in a bottom-up manner and are typically more self-enforcing. While effective norms can significantly enhance performance of individual agents and agent societies, there has been little work in multiagent systems on the formation of social norms. We propose a model that supports the emergence of social norms via learning from interaction experiences. In our model, individual agents repeatedly interact with other agents in the society over instances of a given scenario. Each interaction is framed as a stage game. An agent learns its policy to play the game over repeated interactions with multiple agents. We term this mode of learning social learning, which is distinct from an agent learning from repeated interactions against the same player. We are particularly interested in situ...

• Type: Conference
• Year: 2007
• Where: IJCAI
• Authors: Sandip Sen, Stéphane Airiau
• Keywords: Artificial Intelligence, Behavioral Norms, IJCAI 2007, Social Learning, Social Norms