  Multiagent systems provide a basis of developing systems of autonomous
entities and thus find application in a variety of domains. We consider a
setting where not only the member agents are adaptive but also the multiagent
system itself is adaptive. Specifically, the social structure of a multiagent
system can be reflected in the social norms among its members. It is well
recognized that the norms that arise in society are not always beneficial to
its members. We focus on prosocial norms, which help achieve positive outcomes
for society and often provide guidance to agents to act in a manner that takes
into account the welfare of others.
  Specifically, we propose Cha, a framework for the emergence of prosocial
norms. Unlike previous norm emergence approaches, Cha supports continual change
to a system (agents may enter and leave), and dynamism (norms may change when
the environment changes). Importantly, Cha agents incorporate prosocial
decision making based on inequity aversion theory, reflecting an intuition of
guilt from being antisocial. In this manner, Cha brings together two important
themes in prosociality: decision making by individuals and fairness of
system-level outcomes. We demonstrate via simulation that Cha can improve
aggregate societal gains and fairness of outcomes.
