Prosocial Norm Emergence in Multi-agent Systems

Author:

Mashayekhi Mehdi1ORCID,Ajmeri Nirav2ORCID,List George F.1ORCID,Singh Munindar P.1ORCID

Affiliation:

1. North Carolina State University, Raleigh

2. University of Bristol, Bristol, United Kingdom

Abstract

Multi-agent 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 multi-agent system viewed as an entity in its own right is adaptive. Specifically, the social structure of a multi-agent 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.

Funder

Science of Security Lablet at North Carolina State University

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Software,Computer Science (miscellaneous),Control and Systems Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Norm Augmented Reinforcement Learning Agents With Synthesized Normative Rules;Journal of Cases on Information Technology;2024-07-16

2. The impact of sociality regimes on heterogeneous cooperative-competitive multi-agent reinforcement learning: a study with the predator-prey game;Journal of Experimental & Theoretical Artificial Intelligence;2024-06-12

3. Self-Governing Hybrid Societies and Deception;ACM Transactions on Autonomous and Adaptive Systems;2024-04-20

4. Fleur: Social Values Orientation for Robust Norm Emergence;Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XV;2022

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