RAWL-E adds a maximin-based reward to norm-learning agents and reports fairer, more robust simulated harvesting societies, though several of the gains are statistically weak or built into the reward itself.
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Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents
RAWL-E adds a maximin-based reward to norm-learning agents and reports fairer, more robust simulated harvesting societies, though several of the gains are statistically weak or built into the reward itself.