How do Role Models Shape Collective Morality? Exemplar-Driven Moral Learning in Multi-Agent Simulation

Abstract

Do We Need Role Models? How do Role Models Shape Collective Morality? To explore the questions, we build a multi-agent simulation powered by a Large Language Model, where agents with diverse intrinsic drives, ranging from cooperative to competitive, interact and adapt through a four-stage cognitive loop (plan-act-observe-reflect). We design four experimental games (Alignment, Collapse, Conflict, and Construction) and conduct motivational ablation studies to identify the key drivers of imitation. The results indicate that identity-driven conformity can powerfully override initial dispositions. Agents consistently adapt their values to align with a perceived successful exemplar, leading to rapid value convergence.

Figures (46)

• Figure 1: Motivation of our study: contrasting human moral learning through role models with current AI limitations, and proposing an exemplar-driven framework for moral learning in multi-agent systems.
• Figure 2: Overview of the Exemplar-Driven Moral Learning framework. The green box is the agent's cognitive architecture, comprising defined moral traits and a daily four-stage loop of planning, action, observation, and reflection. The red box shows four distinct games: Role Model Alignment, Collapse, Conflict, and Construction, designed to investigate how agents acquire and adapt moral norms from exemplars in various conditions.
• Figure 3: Changes in average Social Value Orientation (SVO) over time by moral type in Game 1. Shaded areas represent standard deviation across simulation runs.
• Figure 4: Behavioral trends over time by moral type in Game 1. Top: Increase in prosocial behaviors such as alliance formation and food sharing. Bottom: Decrease in antisocial behaviors including exploitation and robbery.
• Figure 5: Moral justifications of selfish agents at early vs. late stages in Game 1.