Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents

• URL: http://arxiv.org/abs/2412.15163v1
• Date: Thu, 19 Dec 2024 18:38:13 GMT
• Title: Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents
• Authors: Jessica Woodgate, Paul Marshall, Nirav Ajmeri,
• Abstract summary: We present RAWL-E, a method to create ethical norm-learning agents. We find that norms emerging in RAWL-E agent societies enhance social welfare, fairness, and robustness.
• Score: 4.891538364735141
• License:
• Abstract: Social norms are standards of behaviour common in a society. However, when agents make decisions without considering how others are impacted, norms can emerge that lead to the subjugation of certain agents. We present RAWL-E, a method to create ethical norm-learning agents. RAWL-E agents operationalise maximin, a fairness principle from Rawlsian ethics, in their decision-making processes to promote ethical norms by balancing societal well-being with individual goals. We evaluate RAWL-E agents in simulated harvesting scenarios. We find that norms emerging in RAWL-E agent societies enhance social welfare, fairness, and robustness, and yield higher minimum experience compared to those that emerge in agent societies that do not implement Rawlsian ethics.

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