Prosocial Norm Emergence in Multiagent Systems

TL;DR

This paper introduces Cha, a framework for the emergence of prosocial norms in multiagent systems that adapt to environmental and structural changes, promoting fairness and societal benefits.

Contribution

Cha uniquely supports continual system changes and incorporates prosocial decision making based on inequity aversion theory, advancing norm emergence research.

Findings

Cha improves societal gains in simulations.

Cha enhances fairness of outcomes.

The framework adapts to environmental and structural dynamics.

Abstract

Multiagent systems provide a basis for 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 viewed as an entity in its own right 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 arising 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.