Collective Learning in Games through Social Networks

This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and gamebased learning (strategy reinforcement). The focus is on cooperative games, in which a coalition of players tries to achieve a common goal. We show that enriching cooperative games with social networks communication can influence learning towards the social optimum under specific conditions on the network structure and on the existing expertise in the coalition.