A bilevel MARL framework with curriculum learning and closed-loop sequential updates learns stable tax policies in multi-group taxation simulations, extending effective game duration by 60.92% and reducing GDP disparities by 44.12% versus baseline.
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Hierarchical Multiagent Reinforcement Learning for Multi-Group Tax Game
A bilevel MARL framework with curriculum learning and closed-loop sequential updates learns stable tax policies in multi-group taxation simulations, extending effective game duration by 60.92% and reducing GDP disparities by 44.12% versus baseline.