Reinforcement Communication Learning in Different Social Network Structures

Understand

Social network structure is one of the key determinants of human language evolution.

• Previous work has shown that the network of social interactions shapes decentralized learning in human groups, leading to the emergence of different kinds of communicative conventions.
• We examined the effects of social network organization on the properties of communication systems emerging in decentralized, multi-agent reinforcement learning communities.
• We found that the global connectivity of a social network drives the convergence of populations on shared and symmetric communication systems, preventing the agents from forming many local "dialects".