Modeling emergence of norms in multi-agent systems by applying tipping points ideas

TL;DR

This paper explores how tipping point theory from social sciences can inform the design of normative architectures in multi-agent systems, aiming to better understand and influence emergent social norms.

Contribution

It introduces a novel approach to incorporate tipping point concepts into normative multi-agent system design, demonstrating potential methods and effects through simulations.

Findings

Tipping point concepts can be effectively integrated into agent-based normative architectures.

Applying these concepts influences the emergence and stability of social norms in simulations.

Different implementation strategies yield varied impacts on norm adoption dynamics.

Abstract

Norms are known to be a major factor determining humans behavior. It's also shown that norms can be quite effective tool for building agent-based societies. Various normative architectures have been proposed for designing normative multi-agent systems (NorMAS). Due to human nature of the concept norms, many of these architectures are built based on theories in social sciences. Tipping point theory, as is briefly discussed in this paper, seems to have a great potential to be used for designing normative architectures. This theory deals with the factors that affect social epidemics that arise in human societies. In this paper, we try to apply the main concepts of this theory to agent-based normative architectures. We show several ways to implement these concepts, and study their effects in an agent-based normative scenario.